Cloud Database – Presplay Cloud Tech*

Machine Learning And Artificial Intelligence, Cloud Computing and 5G Will be the Most Important Technologies in 2022

Presplay — Thu, 18 Nov 2021 11:00:11 +0000

Artificial Intelligence and Machine Learning, Cloud Computing and 5G Will be the Most Important Technologies in 2022, Says New IEEE Study

Thu, November 18, 2021, 11:00 AM·7 min read

Chief information officers, chief technology officers and technology leaders globally surveyed on key technology trends, priorities and predictions for 2022 and beyond

PISCATAWAY, N.J., Nov. 18, 2021 /PRNewswire/ — IEEE, the world’s largest technical professional organization dedicated to advancing technology for humanity, today released the results of “The Impact of Technology in 2022 and Beyond: an IEEE Global Study,” a new survey of global technology leaders from the U.S., U.K., China, India and Brazil. The study, which included 350 chief technology officers, chief information officers and IT directors, covers the most important technologies in 2022, industries most impacted by technology in the year ahead, and technology trends through the next decade. To learn more about the study and the impact of technology in 2022 and beyond, visit https://transmitter.ieee.org/impact-of-technology-2022/.

The most important technologies, innovation, sustainability and the future

Which technologies will be the most important in 2022? Among total respondents, more than one in five (21%) say AI and machine learning, cloud computing (20%) and 5G (17%) will be the most important technologies next year. Because of the global pandemic, technology leaders surveyed said in 2021 they accelerated adoption of cloud computing (60%), AI and machine learning (51%), and 5G (46%), among others.

It’s not surprising, therefore, that 95% agree –– including 66% who strongly agree –– that AI will drive the majority of innovation across nearly every industry sector in the next 1-5 years.

When asked which of the following areas 5G will most benefit in the next year, technology leaders surveyed said:

telemedicine, including remote surgery and health record transmissions (24%)
remote learning and education (20%)
personal and professional day-to-day communications (15%)
entertainment, sports and live event streaming (14%)
manufacturing and assembly (13%)
transportation and traffic control (7%)
carbon footprint reduction and energy efficiency (5%)
farming and agriculture (2%)

As for industry sectors most impacted by technology in 2022, technology leaders surveyed cited manufacturing (25%), financial services (19%), healthcare (16%) and energy (13%). As compared to the beginning of 2021, 92% of respondents agree, including 60% who strongly agree, that implementing smart building technologies that benefit sustainability, decarbonization and energy savings has become a top priority for their organization.

Workplace technologies, Human Resources collaboration and COVID-19

As the impact of COVID-19 varies globally and hybrid work continues, technology leaders nearly universally agree (97% agree, including 69% who strongly agree) their team is working more closely than ever before with Human Resources leaders to implement workplace technologies and apps for office check-in, space usage data and analytics, COVID and health protocols, employee productivity, engagement and mental health.

Among challenges technology leaders see in 2022, maintaining strong cybersecurity for a hybrid workforce of remote and in-office workers is viewed by those surveyed as challenging by 83% of respondents (40% very, 43% somewhat) while managing return-to-office health and safety protocols, software, apps and data is seen as challenging by 73% of those surveyed (29% very, 44% somewhat). Determining what technologies are needed for their company in the post-pandemic future is anticipated to be challenging for 68% of technology leaders (29% very, 39% somewhat). Recruiting technologists and filling open tech positions in the year ahead is also seen as challenging by 73% of respondents.

Robots rise over the next decade

Looking ahead, 81% agree that in the next five years, one quarter of what they do will be enhanced by robots, and 77% agree that in the same time frame, robots will be deployed across their organization to enhance nearly every business function from sales and human resources to marketing and IT. A majority of respondents agree (78%) that in the next 10 years, half or more of what they do will be enhanced by robots. As for the deployments of robots that will most benefit humanity, according to the survey, those are manufacturing and assembly (33%), hospital and patient care (26%) and earth and space exploration (13%).

Connected devices continue to proliferate

As a result of the shift to hybrid work and the pandemic, more than half (51%) of technology leaders surveyed believe the number of devices connected to their businesses that they need to track and manage –– such as smartphones, tablets, sensors, robots, vehicles, drones, etc. –– increased as much as 1.5 times, while for 42% of those surveyed the number of devices increased in excess of 1.5 times.

However, the perspectives of technology leaders globally diverge when asked about managing even more connected devices in 2022. When asked if the number of devices connected to their company’s business will grow so significantly and rapidly in 2022 that it will be unmanageable, over half of technology leaders disagree (51%), but 49% agree. Those differences can also be seen across regions — 78% in India, 64% in Brazil and 63% in the U.S. agree device growth will be unmanageable, while a strong majority in China (87%) and just over half (52%) in the U.K disagree.

Cyber and physical security, preparedness and deployment of technologies

The cybersecurity concerns most likely to be in technology leaders’ top two are issues related to the mobile and hybrid workforce including employees using their own devices (39%) and cloud vulnerability (35%). Additional concerns include data center vulnerability (27%), a coordinated attack on their network (26%) and a ransomware attack (25%). Notably, 59% of all technology leaders surveyed currently use or in the next five years plan to use drones for security, surveillance or threat prevention as part of their business model. There are regional disparities though. Current drone use for security or plans to do so in the next five years are strongest in Brazil (78%), China (71%), India (60%) and the U.S. (52%) compared to only (32%) in the U.K. where 48% of respondents say they have no plans to use drones in their business.

An open-source distributed database that uses cryptography through a distributed ledger, blockchain enables trust among individuals and third parties. The four uses in the next year respondents were most likely to cite in their own top three most important uses for blockchain technology are:

Secure machine to machine interaction in the Internet of Things (IoT) (61%)
Shipment tracing and contactless digital transactions (51%)
Keeping health and medical records secure in the cloud (47%)
Securing connecting parties within a specified ecosystem (47%)

The vast majority of those surveyed (92%) believe that compared to a year ago, their company is better prepared to respond to a potentially catastrophic interruption such as a data breach or natural disaster. Of that majority, 65% strongly agree that COVID-19 accelerated their preparedness.

About the Survey

“The Impact of Technology in 2022 and Beyond: an IEEE Global Study” surveyed 350 CIOs, CTOs, IT directors and other technology leaders in the U.S., China, U.K., India and Brazil at organizations with more than 1,000 employees across multiple industry sectors including banking and financial services, consumer goods, education, electronics, engineering, energy, government, healthcare, insurance, retail, technology and telecommunications. The surveys were conducted October 8-20, 2021.

About IEEE

IEEE is the world’s largest technical professional organization dedicated to advancing technology for the benefit of humanity. Through its highly cited publications, conferences, technology standards, and professional and educational activities, IEEE is the trusted voice in a wide variety of areas ranging from aerospace systems, computers, and telecommunications to biomedical engineering, electric power, and consumer electronics. Learn more.

Best DevOps Monitoring Tools for 2021

Presplay — Tue, 10 Aug 2021 19:55:43 +0000

Development and operations (DevOps) is the merger of practices, tools and cultural philosophies that increases the ability of an enterprise to deliver applications and services more frequently while improving quality and being cost-effective. By evolving and enhancing products at a rapid pace, DevOps enables enterprises to compete proficiently in the market.

Enterprises that implement traditional infrastructure management and software development processes are likely to be left behind in today’s competitive market, as the modern software development lifecycle encompasses multiple, simultaneous stages of development and testing.

A unified team that performs development, testing, and operations functions is of the essence.

The benefits of DevOps include:

Faster innovation, market adoption and business efficiency.
Rapid delivery of releases.
Practices like continuous integration, continuous delivery and monitoring and logging ensure the reliability of deliverables.
Automation and consistency help you develop, operate and manage processes at scale.
A DevOps cultural model enables effective team building.
Retain control and preserve compliance by using configuration management techniques, fine-grained controls and automated compliance policies.

Table of Contents

What are Monitoring Tools in DevOps?

Given the high velocity of development, testing and operations in today’s application lifecycle, frequent code changes are commonplace.

DevOps monitoring tools provide a comprehensive view of a production environment in real-time, automation, and expanded management throughout the application lifecycle – from planning, development and testing to deployment and operations.

When it comes to application and service monitoring, visualizations, real-time streaming and historical replay are critical components. DevOps monitoring enables development teams to quickly and automatically respond to any ruination in the customer experience.

It enables teams to “shift left” to earlier development stages in order to curtail broken production changes. DevOps monitoring tools help teams manage complex development environments at scale while retaining control of the fast nature that is enabled by DevOps.

In this guide, we will dive into all you should know about the top DevOps monitoring tools.

Best DevOps Monitoring Tools

Here are the best DevOps monitoring tools:

SolarWinds AppOptics (Librato)
Sensu Go
Git (GitHub, GitLab and Bitbucket)
Red Hat Ansible Automation Platform
Microsoft Teams

SolarWinds AppOptics (Librato)

SolarWinds AppOptics is an application and infrastructure monitoring solution that offers a fully customizable metrics platform, distributed transaction tracing, host maps, and more than 150 cloud-ready integrations. With full-stack application performance monitoring (APM), you can visualize and troubleshoot application bottlenecks simply and quickly.

Key Differentiators

Infrastructure monitoring enables a 360-degree view of your enterprise infrastructure and provides advanced alerting in real time, host and container maps, and custom infrastructure dashboards.
The solution provides out-of-the-box support for a variety of frameworks and libraries, including Python, Java, Go, .NET, PHP, Scala and Node.js.
SolarWinds AppOptics automatically determines the root cause of application performance problems.
With distributed tracing, exception tracking and live code profiling, you can trace requests across processes, hosts and data centers.
You can introduce any metric into SolarWinds AppOptics and display them along with infrastructure and application metrics.
With multi-dimensional tags, you can filter and group data with ease.
With over 150+ turnkey, cloud-ready integrations, you can obtain data straight from the source. These include AWS and Azure services, Docker, Kubernetes, etc.
You can try SolarWinds AppOptics free of cost for 30 days. The infrastructure and application monitoring package costs $24.99 per host, per month.

Sensu Go

Sensu Go is a turnkey, end-to-end observability pipeline that enables you to collect, filter, and transform monitoring events and send them to a database of choice. The solution delivers monitoring as code on any cloud, helps eliminate data silos, automates service delivery, reduces alert fatigue and enables automation of diagnosis and self-healing, all from a single observability control plane.

Key Differentiators

Offers limitless integrations for monitoring. You can integrate the platforms and tools that your enterprise relies on, including AWS, Azure, Docker, OpenStack, Kubernetes, etc.
Using Sensu Go’s high-performance enterprise datastore, you can monitor thousands of nodes from a solitary cluster.
With Sensu Go’s federation capabilities, you can obtain visibility into globally distributed infrastructure.
Offers comprehensive health monitoring and enables you to collect basic system metrics, custom application metrics and logs. You can integrate with external databases for unified business intelligence (BI).
Offers incident management and real-time alerting via communication channels like email, SMS and Slack. You can customize alert policies with contact routing and event filters.
Provides native support for diagnosis and self-healing — execute custom scripts/trigger service restarts when problems are detected, automate repetitive operations and trigger remediation actions via third-party APIs.
You can automate service discovery
Sensu Go is available free of cost and is best suited to small-sized companies. Sensu Go Pro is available for $3 per node, per month and is perfectly suited to mid-sized environments. Sensu Go Enterprise is available for $5 per node, per month and is designed for large-sized enterprises.

Git (GitHub, GitLab and Bitbucket)

Git is an open source, distributed version control and source code management (SCM) system that is easy to learn, has a small footprint, and offers lightning-fast performance and efficiency.

With the help of the software, you can easily coordinate work among your DevOps team during source code development. The latest source release of Git is version 2.32.0. You can download the software for Windows, Linux/Unix and macOS.

Key Differentiators

Popular offerings of Git repositories as a service include GitHub, GitLab and Bitbucket.
Git’s branching model enables frictionless context switching, role-based codelines, feature-based workflow and disposable experimentation.
Since Git was built to work on the Linux kernel, is written in C and most operations are performed locally, it can effectively handle large repositories in double-quick time.
As a distributed SCM, there is no single point of failure, as you can create a copy of the entire repository.
Git provides data assurance, as checksums are used to verify data integrity.
With staging area, commits can be formatted and reviewed before completion.
GitHub (free) offers the distributed version control and SCM functionality of Git, along with wikis for every project, continuous integration, task management, feature requests and bug tracking.
GitLab (free) is a web-based DevOps lifecycle tool. Its applications include continuous integration (CI/CD), SCM, Auto DevOps, DevSecOps, agile development, value stream management and GitOps.
Bitbucket (now Bitbucket Cloud) is a one-stop destination for project planning and collaboration on code, testing, and deployment. It is available for free (limited users) and in the form of paid plans. Features include pull requests, Bitbucket Pipelines, IP whitelisting, merge checks, code search, issue tracking and Smart Mirroring.

Red Hat Ansible Automation Platform

Red Hat Ansible Automation Platform provides a framework for building and operating information technology (IT) automation at scale. With a visual dashboard, automation tools including certified, reusable content and analytics and role-based access control, you can centralize and control enterprise infrastructure.

The platform’s YAML automation language makes it possible to assess, manage, and share automation content across an organization. With searchable collections of pre-composed modules and roles, you can easily create automation.

Key Differentiators

With standardized and unified IT automation, Red Hat Ansible Automation Platform helps make network management more consistent. You can automate user onboarding, infrastructure provisioning and orchestration, system patching and updating and software installation.

Red Hat Insights provides unified visibility across platforms. With Red Hat Insights, you can detect, analyze and remediate potential software and configuration problems through automatic alerts.

Red Hat Insights provides a reporting provision on the status of automation deployments across multiple clusters.

You can easily access and distribute collections of supported, precomposed content for quick implementation.

The platform provides developers and business users access to automation resources and services.

You can automate security practices and collate the tools used in security activities.

Developers can set up automation to manage, provision and deploy compute infrastructure across environments. By automating processes, you can rapidly move software between testing and production environments.

The STANDARD package is ideal for enterprise IT operations. The premium package is ideal for mission-critical DevOps. Contact Red Hat Ansible for pricing information. You can try the platform free of cost for 60 days.

Microsoft Teams

When it comes to unifying distributed members of your DevOps team, there is no better solution than a Unified Communications as a Service (UCaaS) platform. Microsoft Teams is an UCaaS platform that allows organizations to virtually meet, chat, call, and collaborate.

Microsoft Teams is the free version of Microsoft’s UCaaS offerings and does not include additional Microsoft Office services and applications. That said, the solution is sufficient if all you need is real-time presence monitoring, individual and group chatting and secure online meetings with up to 100 members, for up to an hour at a time.

Key Differentiators

You can set up ChatOps with messaging extensions. You can integrate all the components in your DevOps toolchain. By integrating DevOps tools, these applications will publish content directly into team conversations/individual chats, which enables faster resolution of issues, ease of collaboration, quicker update sharing, and better knowledge dissemination.
Enterprises embedded in the Microsoft tool suite can benefit from Microsoft Teams. You can integrate over 700 applications from the app store to increase team productivity and manage complex projects. You can leverage custom-built applications to address industry-specific needs with the Microsoft Power Platform.
Microsoft Teams is available in 181 markets and 53 languages. Windows, macOS, Android and iOS users can download and implement the solution.
Microsoft Teams is free of cost. Microsoft 365 Business Standard is ideally suited to small- and mid-sized organizations and is available for $12.50 per month/per user (annual commitment). Microsoft Office 365 E3 is best suited to large-scale enterprises and is available for $20 per month/per user (annual commitment).
Microsoft 365 Business Standard and Microsoft Office 365 E3 offer additional perks when compared to Microsoft Teams, including larger meeting participant capacities, longer meeting durations, the ability to record meetings, personal file storage, business email, advanced auditing and reporting and secure cloud storage.

Choosing DevOps Monitoring Tools

SolarWinds AppOptics offers modern infrastructure monitoring, root cause determination of application performance issues, distributed transaction tracing, custom metrics and analytics and several turnkey, cloud-ready integrations. Overall, SolarWinds AppOptics is a handy DevOps monitoring tool.

The Sensu Go observability pipeline provides monitoring for mission-critical systems and is integrated, secure and scalable. The solution offers health checks, custom metrics and logs, alerts and incident management, endpoint management, auto-remediation and monitoring as code. Sensu Go is one of the best DevOps monitoring tools around.

Git is an essential component of DevOps. You can incorporate several services for hosting your Git repositories, including GitHub, GitLab and Bitbucket. If you are looking for a foundation for building and operating enterprise automation at scale, Red Hat Ansible Automation Platform is a fantastic tool.

Microsoft Teams is an excellent solution to connect distributed team members. You can avail of ChatOps, integrate over 700 applications to streamline workflow, build custom applications and host and participate in video conferences.

You can utilize one or more DevOps monitoring tools, so strictly assess each of the tools we detailed and add one or more of them to your DevOps toolchain.

OVERCOMING CLOUD MIGRATION COMMON ISSUES

Presplay — Sun, 30 May 2021 18:38:52 +0000

More than 85% of organizations use cloud platforms for at least one application today. That said, most organizations also face challenges when transitioning to a cloud environment. Find out what some of the most common cloud migration problems are, and how a managed service provider and an end-to-end cloud migration strategy can ensure successful data migration.

WHY BUSINESSES ARE WILLING TO FACE CLOUD DATA MIGRATION CHALLENGES

Few organizations are concerned about the costs of transitioning to the cloud. But the advantages of migrating data to the cloud are exponential.

Virtually every business is willing to bear the short-term pain of migrating to take advantage of the long-term benefits of cloud computing:

Mobility
Cost Savings
Flexibility
Disaster recovery
Scalability
Insight
Security
Autonomous software updates

Though every organization’s business objectives are different, and strategies for moving data to a cloud-based environment also unique, most still face very similar challenges.

In this article, we discuss the top challenges surrounding the cloud migration process, and how you can avoid them.

Monitor metrics on Azure Database for PostgreSQL – Flexible Server

Presplay — Sat, 22 May 2021 13:25:38 +0000

Monitoring data about your servers helps you troubleshoot and optimize for your workload. Azure Database for PostgreSQL provides various monitoring options to provide insight into the behavior of your server.

Metrics

Azure Database for PostgreSQL provides various metrics that give insight into the behavior of the resources supporting the PostgreSQL server. Each metric is emitted at a one-minute frequency, and has up to 93 days of history. You can configure alerts on the metrics. Other options include setting up automated actions, performing advanced analytics, and archiving history. For more information, see the Azure Metrics Overview.

List of metrics

The following metrics are available for PostgreSQL flexible server:

LIST OF METRICS
Metric	Metric Display Name	Unit	Description
active_connections	Active Connections	Count	The number of connections to your server.
backup_storage_used	Backup Storage Used	Bytes	Amount of backup storage used. This metric represents the sum of storage consumed by all the full database backups, differential backups, and log backups retained based on the backup retention period set for the server. The frequency of the backups is service managed. For geo-redundant storage, backup storage usage is twice that of the locally redundant storage.
connections_failed	Failed Connections	Count	Failed connections.
connections_succeeded	Succeeded Connections	Count	Succeeded connections.
cpu_credits_consumed	CPU Credits Consumed	Count	Number of credits used by the flexible server. Applicable to Burstable tier.
cpu_credits_remaining	CPU Credits Remaining	Count	Number of credits available to burst. Applicable to Burstable tier.
cpu_percent	CPU percent	Percent	Percentage of CPU in use.
disk_queue_depth	Disk Queue Depth	Count	Number of outstanding I/O operations to the data disk.
iops	IOPS	Count	Number of I/O operations to disk per second.
maximum_used_transactionIDs	Maximum Used Transaction IDs	Count	Maximum transaction ID in use.
memory_percent	Memory percent	Percent	Percentage of memory in use.
network_bytes_egress	Network Out	Bytes	Amount of outgoing network traffic.
network_bytes_ingress	Network In	Bytes	Amount of incoming network traffic.
read_iops	Read IOPS	Count	Number of data disk I/O read operations per second.
read_throughput	Read Throughput	Bytes	Bytes read per second from disk.
storage_free	Storage Free	Bytes	The amount of storage space available.
storage_percent	Storage percent	Percentage	Percent of storage space used. The storage used by the service may include the database files, transaction logs, and the server logs.
storage_used	Storage Used	Bytes	Percent of storage space used. The storage used by the service may include the database files, transaction logs, and the server logs.
txlogs_storage_used	Transaction Log Storage Used	Bytes	Amount of storage space used by the transaction logs.
write_throughput	Write Throughput	Bytes	Bytes written per second to disk.
write_iops	Write IOPS	Count	Number of data disk I/O write operations per second.

Server logs

Azure Database for PostgreSQL allows you to configure and access Postgres’ standard logs. To learn more about logs, visit the logging concepts doc.

Performance Recommendations in Azure Database for PostgreSQL – Single Server

Presplay — Sat, 22 May 2021 13:19:42 +0000

Applies to: Azure Database for PostgreSQL – Single Server versions 9.6, 10, 11

The Performance Recommendations feature analyses your databases to create customized suggestions for improved performance. To produce the recommendations, the analysis looks at various database characteristics including schema. Enable Query Store on your server to fully utilize the Performance Recommendations feature. After implementing any performance recommendation, you should test performance to evaluate the impact of those changes.

Permissions

Owner or Contributor permissions required to run analysis using the Performance Recommendations feature.

Performance recommendations

The Performance Recommendations feature analyzes workloads across your server to identify indexes with the potential to improve performance.

Open Performance Recommendations from the Intelligent Performance section of the menu bar on the Azure portal page for your PostgreSQL server.

Select Analyze and choose a database, which will begin the analysis. Depending on your workload, th analysis may take several minutes to complete. Once the analysis is done, there will be a notification in the portal. Analysis performs a deep examination of your database. We recommend you perform analysis during off-peak periods.

The Recommendations window will show a list of recommendations if any were found.

Recommendations are not automatically applied. To apply the recommendation, copy the query text and run it from your client of choice. Remember to test and monitor to evaluate the recommendation.

Recommendation types

Currently, two types of recommendations are supported: Create Index and Drop Index.

Create Index recommendations

Create Index recommendations suggest new indexes to speed up the most frequently run or time-consuming queries in the workload. This recommendation type requires Query Store to be enabled. Query Store collects query information and provides the detailed query runtime and frequency statistics that the analysis uses to make the recommendation.

Drop Index recommendations

Besides detecting missing indexes, Azure Database for PostgreSQL analyzes the performance of existing indexes. If an index is either rarely used or redundant, the analyzer recommends dropping it.

Considerations

Performance Recommendations is not available for read replicas.

Next steps

Learn more about monitoring and tuning in Azure Database for PostgreSQL.

Executing the right migration strategy for your IT transformation.

Presplay — Thu, 22 Apr 2021 17:41:43 +0000

While this may seem academic, we have seen organizations spend millions with no results—all because their project lacked focus.

In today’s market place, migrations are frequently referred to as relocations, consolidations, cloud migrations, or hybrid migration. The ability to differentiate between the various types of migrations is fundamental to communicating what you are trying to accomplish. It facilitates a more intelligent conversation within an organization, its stakeholders, executive sponsors, and vendors.

Migration is a general, overarching term describing the process of moving IT systems, workloads, applications, and their infrastructure from their present operating environment to one or more new target environments, e.g., private/public cloud, colocation facilities, edge location, and/or an owned and operated data center.

What type of migration should you execute?

Hybrid
Cloud
Consolidation
Colocation
Relocation

Hybrid

The lines have been blurred between the different types of migrations. Many organizations today require a hybrid enterprise environment where their infrastructure and systems operate across multiple IT landscapes. These landscapes can include owned, leased and operated data centers, various private and public clouds (IaaS, PaaS, SaaS, DRaaS), and colocation facilities. A hybrid enterprise can provision and move applications with great fluidity between various infrastructures to optimize performance, security, and cost. But, the most compelling reason for the hybrid enterprise is the speed with which an enterprise can respond to market opportunities and competitive threats. The IT department is no longer the bottleneck for rolling out new services, it’s the accelerator, dramatically transforming the IT landscape.

Cloud

Cloud migrations move applications, workloads, systems, and infrastructure from a physical and/or virtual environment (p2c, v2c) to a private or public cloud provider, or it moves these systems in between cloud environments.

While not necessarily less expensive than physical infrastructure, cloud infrastructure can transform the enterprise with greater agility and scalability through:

On-demand self service
Broader network access
Resource pooling
Rapid elasticity
Measured/metered services\

Consolidations

Data center consolidations reduce the number of physical data centers and/or the number of servers being used by either decommissioning legacy servers, repurposing servers, and/or the reducing servers via virtualization and/or hyper-converged technology. The goal is to achieve a higher level of density and decreased footprint. In many cases, the physical consolidation of facilities has similar attributes but also includes the sale of the facility, exit from a lease, and/or reuse of the space for other mission critical needs. Here are several of the top benefits:

Less hardware
Power savings
Smaller network
Lower facility costs
Reduced cooling loads
Fewer software licenses
Reduction in manpower

Consolidations are typically driven by server sprawl, mergers and acquisitions, a demand for higher density levels via virtualization, and cost savings from power and cooling consumption.

Colocation/ Relocation

Data center relocations move infrastructure from their current location to a new location. It involves only two data centers: the sending data center (source location) and the receiving data center (target location). These are accomplished in the following manner:

Physical-to- physical (p2p or forklifts)
Physical-to-virtual (p2v)
Virtual-to-virtual (v2v)
Physical-to-cloud (p2c)
Virtual-to-cloud (v2c)

Increasingly, enterprises are electing to collocate in lieu of building new data center facilities. The exceptions are organizations in highly regulated industries with compliance requirements such as banking, health-care, and public utilities.

The decision to build, buy, modernize or collocate a data center(s) is also influenced by an organization’s CapEx or OpEx posture. If the goal is to maximize OpEx, then collocation is smart. If not, CapEx compels a build, buy, or modernize approach depending on variables such as power consumption, cooling, footprint, cost, and timeline to operational readiness.

Relocation success starts with identifying the optimum target location; therefore, site selection is critical.

Migrate with confidence using a proven data center and cloud migration strategy.

Presplay — Mon, 22 Mar 2021 17:46:41 +0000

The Migration Strategy Board helps organizations develop a data center or cloud migration plan. Designed like an interactive game board, it visualizes the five major phases of a data center and cloud migration project.

It includes objectives, deliverables, tools, and additional tips for migrating assets, infrastructure, and services. A methodology specific to migrations helps ensure operational stability, business continuity, and savings.

White Paper

The Cloud and Data Center Migration Methodology

Discover the cloud and data center migration methodology behind the Migration Strategy Board. It is a proven process that migrates physical assets and apps with zero operational disruption. Get insight for your hybrid IT transformation and reduce IT costs.

Migrate physical assets and applications with zero operational disruption.

David-Kenneth Group’s Cloud and Data Center Migration Methodology (DKGm) is a step-by-step, proven process for planning and executing successful migrations. It is intentionally designed to support hybrid IT operating environments. Organized into five phases, it includes a baseline of more than 80 deliverables and two migration-specific toolsets. Below is a summary of each phase.

Five Methodology Phases

Phase 1: Initiation
Phase 2: Discovery
Phase 3: Planning
Phase 4: Execution
Phase 5: Closeout

Phase 1: Initiation

The Initiation Phase launches the project and includes key objectives that lay the groundwork for success. It establishes the business case and project charter, organizes the project team, and is where a high-level migration strategy begins to take shape.

Your key objectives are:

Define enterprise strategy: Identify and document how the cloud and the data center can be a driver of key strategic business initiatives. Also, provide guidelines for cloud adoption, future modernization and optimization initiatives, and other agile technologies.

Develop business case: Identify the goals and objectives (business and technical) for cloud and data center migrations, key performance indicators, risks and benefits, and an ROI analysis for the project. A well-crafted case facilitates institutional buy-in.
Develop project charter: Document project objectives and constraints, what is in and out of scope, the resources involved, milestones, risks, dependencies, and high-level budget estimates. A well-executed charter helps to minimize internal politics.

Select migration approaches: Given your current data center, cloud, colocation, and edge environments, identify potential migration types, taking into consideration security and regulatory compliance. Also include in your evaluation the project teams’ skill sets, which can be a significant cost driver if skill gaps need to be addressed.

Create a plan and schedule: Establish a preliminary timeline, schedule, resource list, and communication plan for stakeholders. It should include the estimated resource costs, the number of sites to be moved, the number of move groups, and the major milestones.
Kick-off migration: Review the project timeline, high-level project goals, set expectations, review roles and responsibilities, articulate the communication plan, and kick off your data center migration project with actionable next steps.

Tips

Solid goals are key.
Set realistic expectations.
Enforce project priorities. They will be tested.
Communicate early and often with stakeholders.

The people in your organization and your customers are the most
critical component of your migration. Communicating a solid plan will build
confidence in the project and help address organizational concerns.

Phase 2: Discovery

The Discovery Phase identifies and documents your physical and virtual environment, inclusive of the application inventory and interdependencies. With a combination of auto and manual data collection methods, discovery identifies critical data at the business, application, and infrastructure layers.

The goal is to create a Master Asset Library (MAL), a repository for asset data and the authoritative source for the migration.

It includes the following objectives:

Collect documentation: Collect and consolidate all existing documentation from each business unit, via your databases (CMDB/CMS), diagrams, facility documentation, contracts, etc.
Deploy auto-discovery tool: Deploy an auto-discovery tool to capture data across your operating environment and into the cloud, from application workloads to data lurking at the edge.
Map dependencies: Identify interdependencies across the business, application, and infrastructure layers (network, cloud, compute, and storage). Also capture traffic flows between server, storage, and network assets daily, weekly, monthly, quarterly, and during other seasonal events.

Distribute questionnaires: Use questionnaires to collect otherwise “undiscoverable” information from server and application owners, resolve gaps from auto-discovery, and understand data points that machines cannot uncover, i.e., maintenance windows, application owners, hard-coded IP addresses, security concerns, etc.
Conduct interviews: Interview server and application owners to resolve gaps, address external partner and cloud connections, capture undocumented requirements, and address special situations brought to attention by the questionnaires.

Do manual inventory and site audit: Validate auto-discovered data and capture any assets that were not auto-discoverable. Gather information needed for the floor plan, rack elevation, and patch diagrams.
Consolidate asset data: Consolidate auto- and manual-discovery data into a single repository of truth, aka the MAL, and keep it current with regular scans, including the integration of operational activities with your change control board.

Tips

Don’t get stuck in discovery. If you document too much, you risk budget and schedule overruns.
Different situations require gathering different information. For example, some undocumented assets may only be known by select stakeholders.
Do not forget to gather business information, i.e., TCO, ROI, SLAs, service windows, refresh.

Organizations discover undocumented IT assets and dependencies 100%
of the time and typically experience a +20% variance between what is known and what is discovered.

Phase 3: Planning

The Planning Phase is where the team determines dispositions and performs move-group planning. The project plan and schedule evolve into the master plan for execution. During this phase a clear and consolidated picture of what will be necessary during the execution phase takes shape.

Here are the objectives:

Application workload placement: Use your discovery data to categorize and prioritize workloads to assess best-fit placements. Be certain to carefully weigh the implications of any application infrastructure modifications, i.e., rehost, re-platform, repurchase, refactor, retire, and retain. Evaluate and select a cloud service provider(s), ensuring organizational requirements, regulatory requirements, data controls, and compliance laws (GDPR, SOX, PII) are supported.

Determine dispositions: Use discovery data and business drivers to select the end-state disposition of physical assets and applications where it can optimally function and service the business. A hybrid mix of dispositions is typical as some systems are not cloud-ready or cloud-fit.

Create move groups: Analyze data in the MAL to understand interdependencies between transactions, services, IP, systems, applications, networks, compliance regulations, and hardware. Establish the move groups and move dates, and for a quick win, identify migration pilot group(s) to test and optimize, ensuring that at least one of every migration disposition planned is included.

Modernize and optimize infrastructure: Identify the current state of your infrastructure (as-is), the ideal future state (to-be), and the temporary transition state necessary between them. Align with business, budget, and timeline objectives to remediate necessary gaps and issues. Design (high-level and low-level designs), procure via a bill of materials (BOM), build, and configure your target state IT infrastructure environment.
Modernize and optimize cloud: Ensure you are fully leveraging the agility and elasticity of the cloud by updating operational processes and procedures.

Formulate test plans: Migration testing must validate that the new infrastructure and cloud services continue to deliver the same services and performance. Tabletop, infrastructure, application, user acceptance, and latency testing are optimal.

Develop move plans: Sequence all the move groups on a timeline for the migration. Review and verify the move plan schedule with the business stakeholders to ensure no negative impacts. Don’t forget logistical and backup planning.

Plan data management: Compartmentalize the data in the cloud environment to control access, ensure compliance requirements are in place/configured, and mitigate security risks.
Mitigate migration risks: Mitigate potential migration risks and issues with contingency dates, rollback plans, backup resources, a clear chain of command for quick decisions, enforced change control, and other elements that establish a robust fault-tolerant plan.

Prepare target data center locations: Upgrade and install in advance the power, circuits, cooling, and cabling infrastructure. Ready all the new equipment in the target location and validate it performs to specification via ready-for-use (RFU) testing before any migrations can begin.
Prepare target cloud provider: Configure the initial cloud setup for users, billing, resource hierarchy, access control, networking configuration, monitoring, security, compliance, and other basic set-up requirements before the first service is hosted to avoid future re-work and issues. Architect and design your target cloud environment much like you would your data center taking into account needs for high availability and redundancy. The cloud is not an excuse for poor design and is not a panacea with built-in redundancy. It must be designed.

Tips

Creative timing and groupings can simplify or reduce costs.
Procurement is often a critical path, especially for new circuits.
Have a fallback window and a plan B. Do not be afraid to use them.

Smart simplicity and creative problem solving can resolve
challenges—like unsupported assets, security gaps,
and more—without disrupting the timeline or the budget.

Phase 4: Execution

A data center or cloud migration is 75 percent planning and 25 percent execution. Thorough planning and preparation are your best protection against migration risks. Pre-migration testing, pilot migrations, contingency rollback planning, and detailed cutover run books support the final go or no-go decision as the gatekeeper for execution readiness. Post-testing, acceptance criteria, and solid issue tracking ensure you do not walk away from the scene with a hidden bomb still ticking.

Below are the crucial steps to the Execution Phase:

Complete pre-migration tests: Utilize pre-migration testing as a baseline for post-migration performance, and identify errors or performance issues already present in the system. Course-correct before initiating a migration.
Execute data center pilot migration(s): Use pilot migrations as an opportunity to build support and trust internally by migrating low-complexity, low-risk workloads. Utilize the same key steps for large groups, optimizing processes and procedures, and documenting lessons learned. Similarly, migrate non-production environments before their production equivalent to refine and monitor the success of the cutover process.
Execute cloud pilot migrations: Test migration tools for status tracking, performance evaluation, and cost-effectiveness against the metrics defined in the business case. Map out any solutions for bottlenecks before they become an issue with a production system
Run data center backups: Establish and execute a backup plan to ensure a full restore is possible in the event of total equipment failure or data loss during migration.
Run cloud backups: Confirm that business-critical data and applications in the cloud are recoverable and within the allowable timeframe.
Decide go/no-go: Make a go/no-go decision about whether to execute the migration. This decision is made jointly by a designated team of decision-makers comprised of core project team members.

Execute migration: Execute the migration based on the migration plan and run book. Enforce a clear chain of command and responsibilities, capturing and managing any issues as they emerge.

Complete post-migration testing: Run infrastructure test scripts on storage devices and servers to ensure a healthy connected environment, then hand off for business user acceptance testing of databases and applications. Finally, closely monitor applications in production for the next 24 hours for any necessary performance tuning.
Conclude support period: Keep the migration support desk open to ensure full stabilization of the system and to address issues that can surface a week or so post-migration.

Tips

Bigger moves can be easier than small ones.
Migrate from steady-state to steady-state.
Do not underestimate the test planning effort.

Triggering your contingencies and maintaining control can make
a critical difference when the plan does not go as planned.

Phase 5: Closeout

After completing the complex undertaking of migration, the Closeout Phase can catch organizations by surprise with hidden risks and expenses, and it can take longer than anyone expects.

Below are the objectives:

Decommission assets & space: Track the inventory of remaining assets and develop a strategy for decommissioning them. Assets may be liquidated, retired, or resold. Review your lease agreement and building and facility services contracts. Establish a termination plan for services at the previous facility, restore and clean the site, and protect or destroy any sensitive materials.
Establish operations: Ensure that regular operations’ staff are familiarized with the new environmental responsibilities and skill gaps are remediated, and fully return operational activities to them. Also, integrate DevOps and update the governance model including infrastructure and data standards for the cloud. Define the customer interface for cloud services. To ensure business continuity, review DR plans with the newly transformed environment. Establish strong governance for cloud capabilities and attributes with future cloud applications, services, and monitoring capabilities in mind.

Optimize infrastructure: Continuously monitor, measure, and improve procedures and procedures to ensure responsiveness to business dynamics and needs. Do not hesitate to terminate cloud instances that are not fully utilized or no longer serve their purposes(s). Remember to identify KPIs as a baseline for ongoing infrastructure optimization, modernization, and cost control comparison.
Optimize cloud: Monitor cloud utilization and costs across internal and external platforms and develop a capacity-planning process that keeps the cloud rightsized. For ongoing cleanup and containment, establish audit levels and a cloud adoption framework.

Update contracts and SLA agreements: Manage relationships with stakeholders as you update contracts and SLA agreements, and ensure all details are reflected in new agreements.
Conduct debrief & close project: Change inevitably brings about lessons learned. Review the project with stakeholders and capture, document, and mitigate any issues. Take this opportunity to also document new design considerations discovered during the migration project. Review key success metrics, document findings, show savings, and package these data points into a debriefing report. Invite the sponsors to review and accept the deliverables.

Tips

If the disaster recovery of primary critical systems is not working well, now is the time to correct it while the right team is assembled.
Absorb valuable information gained from the migration project into the organization and tools.
Publish lessons learned as a record for future migration projects.

Done right, significant value and expense can be saved in the closeout phase.

The Bottom Line about Cloud and Data Center Migrations

A data center and cloud migration can fundamentally transform how you deliver IT services and yield an attractive return on investment for IT and business operations. But, you need a rock-solid migration plan, tailored to your operating environment, to get you there.

A methodology specific to migrations will help you create the plan and achieve the transformative results you are looking for while ensuring operational stability in the process.

Google Cloud Certification for Microsoft Database Engineer

Presplay — Sun, 21 Mar 2021 19:37:15 +0000

Introduction

I recently passed the Google Cloud Professional Data Engineer certification exam, Professional Data Engineer Certification. It took me about five month to prepare for this, and I would like to share my thoughts of why I decided to take it on and how I prepared for it.

At the moment, Google cloud (GCP) is a distant third after Amazon (AWS) and Microsoft (Azure) . Google Cloud has also lost money every year since its inception. However, there are several reasons why someone with no prior Cloud (and Open source software technologies) experience might consider taking Google Cloud Certification.

New software projects often launched on Google Cloud (GCP)

I could see from the job postings in the San Francisco Bay Area, where I live and work, that many startups, professional consulting companies, and even larger established enterprises are looking for GCP expertise, when launch or migrate their applications into a cloud.

Google’s Implementation of Open Source Software Technologies

Being deeply engaged with the Microsoft Business Intelligence Stack for a while, I feel that I have missed all that buzz about Open Source technologies, such as Apache AirBeam (data pipelines and workflows), Apache AirFlow (integration of data pipelines with other services), and Apache Kafka (streaming data). Google Cloud appeared later, so it has the latest and, sometimes more efficient, implementations of Open Source technologies compared with AWS or Azure.

Deep discount pricing on services

It’s hard to compare pricing between Google Cloud and the other cloud providers because each one has various discounts based on customers’ particular situations. As a database engineer, my strong interest is in databases with batch and streaming processing. Those services, especially a data warehouse implementation, are expensive to use on all three cloud providers. GCP makes it seem more affordable than the other providers.

Plenty of preparation material

The GCP exams (e.g. Google Cloud Professional Data Engineer) have been around since 2018. There is a lot of preparation material, but it’s evolving since the exam was updated in 2019. It’s important to find and use the latest updates. Here are a few resources:

Exam preparation Book – Official Google Cloud Certified Professional Data Engineer Study Guide
Online Coursera preparation classes.
https://www.qwiklabs.com/ – GCP labs make the experience quite enjoyable!

My study routine

I have had no prior cloud experience before embarking on this learning journey, so my first step was to sign up with the Coursera Data Engineering with Google Cloud Specialization class, for a monthly fee of $USD 50.

The class is divided into six modules starting with cloud fundamentals. Each module includes Google Cloud labs, knowledge tests and instructional videos led by Google engineers. It’s important that the entire curriculum was developed together with Google. I was studying two hours a day, and I was able to finish all six modules within two months. The Coursera class gave me about 40% of knowledge needed to pass the actual exam.

While spending time on Coursera classes, I purchased the Official Google Cloud Certified Professional Data Engineer Study Guide book for $USD 50. The book is overwhelming at first, but the author has a knack of breaking rather complicated material into a set of rather simple statements. The book comes with its own set of sample exam questions. I was reading and studying this book continuously. Additional benefit of having this book was that it could be used as a cross reference between Coursera class material and the exam itself. The book gave about 30% of knowledge needed to pass the actual exam.

One of my best ‘finds’ was QuickLabs.com. The company is owned by Google itself and provides you with an actual experience of working on Google Cloud. There are several hundreds of labs with different levels of difficulty and durations from 30 min to 1 hour 30 min. For a monthly fee of $USD 55, I tried to finish one lab a day for 2 months. The labs provided remaining 30% of knowledge needed to pass the actual exam.

Also, worth mentioning, the wide availability of sample exam questions (search web for `gcp exam dumps`) on the various sites and forums. The one big problem I discovered, was that the answers in most cases were incorrect.

Overall you will learn:

Differences between SQL and Non-SQL databases : logical, physical architecture, when to use
Alternative SQL databases (in addition to SQL Server) and when to use them: Cloud SQL, Cloud Spanner, BigQuery
Data Warehouse implementation (BigQuery) with features comparable to Microsoft Azure and Amazon AWS
Streaming vs batch processing of data
Data pipelines implementation as an alternative to Microsoft Integration Services (SSIS) packages.
Basics of Machine Learning (ML) and Artificial Intelligence (AI)

Conclusion

I hope that this short article provides you with enough motivation to consider Professional Data Engineer Certification) certification as well as ready-to-use updated list of exam preparation materials.

Oracle Extends Database Leadership with Oracle Database 21c

Presplay — Wed, 13 Jan 2021 03:11:44 +0000

Introduces more than 200 new innovations, further advancing Oracle’s converged database engine

Automated machine learning easily runs inference directly on the database

Free, native blockchain tables provide secure audit trail on transactions and processes

Persistent memory support delivers breakthrough operational database performance

NEWS PROVIDED BY

Oracle

Jan 13, 2021, 11:00 ET

AUSTIN, Texas, Jan. 13, 2021 /Presplaycloud/ — Oracle announced that Oracle Database 21c, the latest version of the world’s leading converged database, is available on Oracle Cloud, including the Always Free tier of Oracle Autonomous Database. Oracle Database 21c contains more than 200 new innovations, including immutable blockchain tables, In-Database JavaScript, native JSON binary data type, AutoML for in-database machine learning (ML), and persistent memory store, as well as enhancements for in-memory, graph processing performance, sharding, multitenant, and security. Unlike other vendors’ single-purpose databases in the cloud or on-premises, Oracle Database 21c provides support for multi-model, multi-workload, and multi-tenant requirements – all within a single, modern converged database engine. In addition, Oracle today announced the availability of Oracle APEX (Application Express) Application Development, a new low-code service for developing and deploying data-driven enterprise applications quickly and easily. The browser-based, low-code cloud service enables developers to create modern web apps for desktops and mobile devices using an intuitive graphical interface.

“Oracle Database 21c continues our strategy of delivering the world’s most powerful converged database engine,” said Andrew Mendelsohn, executive vice president, database server technologies, Oracle. “It provides leading JSON document processing performance. It provides breakthrough operational database performance with Intel^® Optane Persistent Memory support. It provides industry-leading analytic database capabilities with new Self-Managing In-Memory Column Store, highest performance graph processing, and AutoML for simplest machine learning model development. It provides Immutable Blockchain Tables for tamperproof SQL tables. Competing vendors require separate JSON document, operational, analytic, graph, ML, and blockchain databases and services to support these capabilities. Oracle’s converged database approach makes developers far more productive when building new applications, and makes it easy to later evolve applications to meet new business requirements.”

What Analysts are Saying about Oracle Database

“With the launch of Database 21c, Oracle has elevated its flagship database to a new level of convergence with broad support for a wide variety of data types and workloads,” said Carl Olofson, Research Vice President, Data Management Software, IDC. “The 200 new built-in innovations, including immutable blockchain tables and AutoML for in-database machine learning, elevate Oracle Database 21c to a new level of functionality, eliminating the need for specialized, isolated cloud services and tools to do those jobs. Users can avoid the compounding of costs and operational complexity that comes with each additional cloud service that organizations ordinarily use. In this way, Oracle is effectively slicing away at this disjointed set of services with a simplified, more technically elegant, and integrated approach that is far better suited for the enterprise needs of 2021.”

“Oracle’s latest converged database—Database 21c—focuses on making life dramatically easier for both users and developers. It supports and integrates an expanded range of data models and workloads, and includes built-in machine learning to eliminate the need for separate tooling and services by enabling organizations to run inference directly on their database, right next to their data. This is a refreshing contrast for organizations that leverage the likes of AWS, which has more than a dozen different databases, each requiring customers to deal with different APIs, ETL approaches and data integration processes. Oracle Database 21c transcends the barriers of a multi, isolated, and intrinsically non-converged, database approach,” said Mark Peters, Principal Analyst & Practice Director, ESG.

What Customers are Saying about Oracle Database

Headquartered in London, Aon is a US$46B global professional services firm providing a broad range of risk, retirement and health solutions. “We’ve never been able to see all of our Oracle sales and marketing data in one, unified system. It’s a real milestone. Using Oracle Autonomous Data Warehouse and Oracle Analytics Cloud, we’ve seen performance boosted by 50X to 60X that makes response times to complex sales queries from 500 power users much faster and analytics costs are significantly lower than our on-premises business intelligence tools,” said Liesbeth Mulder, Global Reporting Lead, Aon.

Angelini Pharma is one of the largest pharmaceutical companies in Italy. “The Quinaryo XRing solution has been an important step ahead in our IoT strategy to experiment with a wearable device integrated with a data security tool based on a blockchain table solution,” said Pietro Berretoni, Digital & Innovation Head, Angelini Pharma. “With Oracle Blockchain Tables, the solution provides tamper-proof records that can easily integrate with other applications without requiring a complex new infrastructure. Oracle Database includes all the tools we know and new features like Oracle Blockchain Tables that we can leverage with XRing for sensible data collection.”

New Innovations in Oracle Database 21c

Oracle Database 21c is the database engine that powers Oracle database services in the cloud and on-premises, including Oracle Autonomous Database, Oracle Exadata Database Service, Oracle Exadata Database Cloud@Customer, and Oracle Exadata Database Machine. The latest release includes more than 200 new innovations, which extend database convergence to new use cases, optimize performance, and improve developer, analyst, and data scientist productivity. Key innovations include:

Immutable Blockchain Tables: Blockchain Tables bring the key security benefits of blockchain technology to enterprise applications. Part of Oracle’s Crypto-Secure Data Management, Blockchain Tables provide immutable insert-only tables whose rows are cryptographically chained together. By providing tamper detection and prevention capabilities directly in the Oracle Database, customers can protect against illicit changes by insiders or hackers impersonating administrators or users. Blockchain Tables are part of the converged database, accessed with standard SQL, and support full analytics and transactions – making it orders of magnitude easier to use, and more functional, than existing blockchain implementations. Blockchain Tables are a free feature in all Oracle Database editions.
Native JSON Data Type: Oracle has provided powerful SQL/JSON query and indexing support for many years. Database 21c adds a new JSON data type representation, enabling up to 10x faster scans and up to 4x faster update operations. Overall, these improvements make Oracle SQL/JSON 2x faster than MongoDB and AWS DocumentDB on the YCSB benchmark. As with previous releases, users can mix or join JSON and other data types; index any JSON element for fast OLTP; use declarative parallel SQL analytics across all formats; and run complex joins across multiple JSON documents and collections—all without any need for custom application code.
AutoML for In-Database Machine Learning: Automatically builds and compares machine-learning models at scale, and facilitates the use of machine learning by non-experts. A new AutoML user interface makes it easier for non-expert users to leverage in-database machine learning. Oracle also added new algorithms for anomaly detection, regression, and deep learning analysis to our extensive library of popular, in-database machine learning algorithms.
In-Database JavaScript: Enables developers to work efficiently in modern programming languages. The embedded Graal Multilingual Engine allows JavaScript data processing code to run inside the database – where the data resides – eliminating expensive network round-trips. In addition, users can easily execute SQL from within JavaScript code, and JavaScript data types are automatically mapped to Oracle Database data.
Persistent Memory Support: Stores database data and redo logs in local Persistent Memory (PMEM), which significantly improves the performance of IO-bound workloads. SQL runs directly on data stored in the direct-mapped Persistent Memory file system, eliminating the IO code path and the need for large buffer cache. In addition, new database algorithms prevent partial or inconsistent stores to Persistent Memory.
Higher Performance Graph Models: Allows modelling of data based on relationships, and enables exploration of connections and patterns in social networks, IoT, and more. Further improvements in memory optimization reduce the amount of memory required to analyze larger graphs, which enables existing applications to run faster with no changes. In addition, users can create or extend graph algorithms using Java syntax, which can execute as native algorithms since they are compiled with the same optimizations.
Database In-Memory Automation: Oracle supports both row and column formats in the same table to allow analytics and transactions to run simultaneously on the same table. Oracle Database 21c introduces a Self-Managing In-Memory Column Store that simplifies and improves efficiency by automatically managing the placement and removal of objects in the In-Memory Column Store, then tracks usage patterns and moves and evicts objects from the column store. In addition, columns are automatically compressed based on usage patterns. Oracle Database 21c also introduces new in-memory vector join algorithms to speed up complex queries.
Sharding Automation: Native Database Sharding delivers hyperscale performance and availability while enabling global enterprises to easily meet data sovereignty and data privacy regulations. Data shards share no hardware or software, and can reside on-premises or in the cloud. To simplify the design and use of sharding, Oracle Database 21c includes a Sharding Advisor Tool that assesses a database schema plus its workload characteristics and then provides a sharded database design optimized for performance, scalability, and availability. Backup and Recovery across shards is also automated.

Hear what customers, partners, and analysts are saying about the new Oracle Database 21c.

About Oracle
Oracle offers suites of integrated applications plus secure, autonomous infrastructure in the Oracle Cloud. For more information about Oracle (NYSE: ORCL), please visit us at oracle.com.

Additional Resources

Watch Oracle Live with Andy Mendelsohn
Get an in-depth look at the latest database innovations
Learn more about Oracle Database 21c
Try Oracle Database for free

Trademarks
Oracle and Java are registered trademarks of Oracle Corporation.

SOURCE Oracle

IBM Has a Lot to Prove this year

Presplay — Tue, 12 Jan 2021 02:50:32 +0000

Many tech stocks have soared as markets recovered from the pandemic-driven sell-off early last year. IBM (NYSE:IBM) is an exception. The century-old tech giant was already disliked by investors before the pandemic as it slogged through a multiyear turnaround; the company’s results have deteriorated since, as customers pull back on spending amid unprecedented uncertainty.

IBM’s fourth-quarter report last week sent the stock down around 10% on Friday, erasing the gains logged so far this year. While there were some green shoots in IBM’s results, it’s clear that the company has a lot of work to do to win over investors this year.

IMAGE SOURCE: GETTY IMAGES.

Tumbling revenue and profit

IBM’s total revenue for the fourth quarter sank 6% to $20.4 billion; it was down 8% adjusting for divested businesses and currency. All of IBM’s segments struggled. The cloud and cognitive software segment, which houses some of IBM’s key cloud and artificial intelligence (AI) products, suffered a 7% sales decline. That was entirely due to a 26% plunge in sales of transaction processing products.

The services businesses fared no better. Global business services sales were down 5%, while global technology services sales were down 8%. “Our performance reflects the fact that our clients continue to deal with the effects of the pandemic and broader uncertainty of the macro environment,” said CEO Arvind Krishna during the earnings call.

The bottom line took a big dive thanks to lower revenue and a large restructuring charge. Adjusted earnings per share tumbled 56% to $2.07.

A return to growth this year

It wasn’t all bad news for IBM. Total cloud revenue grew by 10% during the quarter to $7.5 billion, pushing cloud revenue for the full year up to $25.1 billion. Red Hat also performed well, with normalized revenue soaring 19% from the prior-year period. The debt from the Red Hat acquisition is being quickly brought down, with IBM reducing its total debt load by $3.9 billion in the fourth quarter alone.

IBM expects to produce revenue growth in 2021 as spending from clients recovers, and as the company’s hybrid cloud and artificial intelligence initiatives take hold. IBM also expects to produce between $11 billion and $12 billion of free cash flow for the year, excluding cash spending related to restructuring and the planned spinoff of the managed infrastructure services business. The company logged $10.8 billion of free cash flow for 2020.

Krishna explained in the earnings call: “In 2021, the significant changes we have made to focus on hybrid cloud and AI will also begin to take hold. The company will look different at the end of the year, particularly with the execution of the spinout, but also with the operational changes to sharpen our focus.”

Time is not on IBM’s side

IBM has been transforming itself for the better part of a decade at this point. A return to sustainable growth has proved elusive. The acquisition of Red Hat in 2019 and the managed infrastructure services spinoff are the two biggest moves the company has made so far, and IBM is undoubtedly a leader in the hybrid cloud market that it sees as a $1 trillion opportunity. But there’s been little in the way of improved financial results, which is what the market cares about.

Revenue growth this year isn’t going to be enough on its own to convince investors that the IBM turnaround story is worth investing in. The bar is low: Revenue slumped 5% in 2020 as the pandemic raged. IBM needs to convince investors that its return to growth is for real this time, driven by its bets on hybrid cloud computing, artificial intelligence, blockchain, and other growth areas. Another temporary return to growth isn’t going to cut it.

For patient investors who believe in IBM’s strategy, the stock has a lot to offer. It now trades for just 9.5 times the low end of the company’s free cash flow guidance for 2021, and it sports a dividend yield of 5.5%. There’s a strong value case to be made for IBM; whether it works out for investors in the long run depends on the company’s all-in bet on hybrid cloud computing paying off.

Cloud Database – Presplay Cloud Tech*

Machine Learning And Artificial Intelligence, Cloud Computing and 5G Will be the Most Important Technologies in 2022

Artificial Intelligence and Machine Learning, Cloud Computing and 5G Will be the Most Important Technologies in 2022, Says New IEEE Study

Best DevOps Monitoring Tools for 2021

What are Monitoring Tools in DevOps?

Best DevOps Monitoring Tools

SolarWinds AppOptics (Librato)

Sensu Go

Git (GitHub, GitLab and Bitbucket)

Red Hat Ansible Automation Platform

Microsoft Teams

Choosing DevOps Monitoring Tools

OVERCOMING CLOUD MIGRATION COMMON ISSUES

WHY BUSINESSES ARE WILLING TO FACE CLOUD DATA MIGRATION CHALLENGES

TOP 8 CLOUD MIGRATION CHALLENGES AND PROBLEMS

– SECURITY & PRIVACY

– DOWNTIME

– LACK OF STRATEGY

– INTEROPERABILITY

– COST

– ADAPTABILITY

– CAPABILITY

– BANDWIDTH

Monitor metrics on Azure Database for PostgreSQL – Flexible Server

Metrics

List of metrics

Server logs

Recommended content

Backup and restore in Azure Database for PostgreSQL – Flexible Server

Logical decoding – Azure Database for PostgreSQL – Single Server

Monitor and tune – Azure Database for PostgreSQL – Single Server

Logical replication and logical decoding – Azure Database for PostgreSQL – Flexible Server

Limits – Azure Database for PostgreSQL – Flexible Server

Extensions – Azure Database for PostgreSQL – Flexible Server

Query Performance Insight – Azure Database for PostgreSQL – Single Server

Compute and Storage Options – Azure Database for PostgreSQL – Flexible Server

Performance Recommendations in Azure Database for PostgreSQL – Single Server

Permissions

Performance recommendations

Recommendation types

Create Index recommendations

Drop Index recommendations

Considerations

Next steps

Recommended content

Logical replication and logical decoding – Azure Database for PostgreSQL – Flexible Server

Limits – Azure Database for PostgreSQL – Flexible Server

Planned maintenance notification – Azure Database for PostgreSQL – Single Server

Logical decoding – Azure Database for PostgreSQL – Single Server

Backup and restore in Azure Database for PostgreSQL – Flexible Server

Overview of business continuity with Azure Database for PostgreSQL – Flexible Server

Query Performance Insight – Azure Database for PostgreSQL – Single Server

Executing the right migration strategy for your IT transformation.

What type of migration should you execute?

Hybrid

Cloud

Consolidations

Colocation/ Relocation

Migrate with confidence using a proven data center and cloud migration strategy.

The Cloud and Data Center Migration Methodology

Migrate physical assets and applications with zero operational disruption.

Phase 1: Initiation

Tips

The people in your organization and your customers are the most critical component of your migration. Communicating a solid plan will build confidence in the project and help address organizational concerns.

Phase 2: Discovery

Tips

Organizations discover undocumented IT assets and dependencies 100% of the time and typically experience a +20% variance between what is known and what is discovered.

Phase 3: Planning

Tips

Phase 4: Execution

Tips

Triggering your contingencies and maintaining control can make a critical difference when the plan does not go as planned.

Phase 5: Closeout

Tips

Done right, significant value and expense can be saved in the closeout phase.

The Bottom Line about Cloud and Data Center Migrations

Google Cloud Certification for Microsoft Database Engineer

Introduction

New software projects often launched on Google Cloud (GCP)

Google’s Implementation of Open Source Software Technologies

The people in your organization and your customers are the most
critical component of your migration. Communicating a solid plan will build
confidence in the project and help address organizational concerns.

Organizations discover undocumented IT assets and dependencies 100%
of the time and typically experience a +20% variance between what is known and what is discovered.

Triggering your contingencies and maintaining control can make
a critical difference when the plan does not go as planned.