devopsy.kinsta.cloud

Author: Mike Vizard

Atlassian Extends Open DevOps Ambitions

At an online Atlassian Team 2021 event this week, Atlassian launched a two-pronged effort to provide organizations with more insights into software development workflows constructed using tools from multiple vendors.

Suzie Prince, head of product for Atlassian, said an Open DevOps initiative will tighten integration between the Jira project tracking and management tools provided with Atlassian and a wide range of tools commonly employed by DevOps teams. The goal is to not only make it easier to correlate issues that are listed in Jira with artifacts found in various software platforms, but also to collect data from DevOps tools to automatically update Jira.

That data will then be employed to inform the key performance indicators (KPIs), based on graphs that Atlassian provides within Jira, to keep track of value streams. Rather than having to acquire a separate value stream management (VSM) platform to track software development progress, the insights needed to understand the impact of, for example, a delay to one project becomes a dividend of using Jira.

At the same time, Atlassian is moving to making it easier for other stakeholders in an organization to track software development projects. A Jira Work Management application is specifically designed for business users that require a higher-level tool to track projects. At the same time, Atlassian revealed this week it has acquired ThinkTilt, a provider of low-code application development tools optimized for Jira.

Atlassian for the first time this week revealed that half of Jira users are not software developers. As organizations increasingly appreciate the degree to which they are now dependent on software to drive digital business transformation initiatives, Atlassian is adding a set of project tracking applications designed specifically for users that need to consume Jira data in a more intuitive fashion.

Prince said Atlassian is committed to making it simple to replace one DevOps tool integration for another with a single click. Rather than requiring organizations to standardize on a single DevOps platform, Prince added that developers will be able to continue to rip and replace tools and platforms as they see fit without compromising visibility into application development workflows.

In addition, the integrations being provided by Atlassian will reduce the time and effort required to configure all the tools that make up a DevOps workflow, from roughly 60 steps today to about six.

As DevOps workflows become more pervasive, the way organizations operate is fundamentally changing. Formal product launches are giving way to a steady stream of software updates that add new capabilities to any platform with little to no fanfare. End users ranging from sales teams to custom support personnel now need to track updates to platforms more closely as new capabilities are continuously added.

Of course, not every organization has the same level of maturity. However, as competitors start to add new features to rival offerings, it is now only a matter of time before most business processes – that increasingly revolve around software updates – begin to evolve and change. As the pace of software development continues to accelerate, the pressure on legacy business processes will only continue.

April 30, 2021
JFrog Tightens Integration with Cloud Edition of Jira

JFrog this week announced that its DevOps platform, delivered as a software-as-a-service (SaaS), can now be integrated with the Jira project tracking and management application, delivered as a cloud service, from Atlassian.

Casey O’Mara, vice president of worldwide business development for JFrog, said this bidirectional integration makes it possible to link a Jira issue, such as a bug fix, to the binary or build residing in the JFrog Artifactory repository that is part of the JFrog DevOps Platform.

Available via an application that can be downloaded from the Atlassian Marketplace, this integration extends an existing alliance between the two companies, said O’Mara. There is, for example, already an integration between Atlassian Bitbucket Cloud for continuous integration and JFrog Artifactory repository.

Creating a link with a Jira issue will make it easier to collaborate by, for example, making it easier to understand why a specific version of an artifact, such as a container image, was created, added O’Mara.

Artifactory is already able to collect issue key messages from Git that logged alongside builds. The Artifactory dashboard for build information displays a link to each of the referenced Jira issues in the Issues tab. Now, users of Jira can link to the builds in Artifactory.

Jira remains the dominant project tracking and management application for software development. As more organizations appreciate the degree to which they now depend on software, O’Mara noted the number of stakeholders in an organization using Jira is starting to increase, as application development schedules are tracked more closely. Atlassian is now making Jira more accessible as a cloud service to help foster that increased adoption, noted O’Mara.

Atlassian is now making a case for transitioning its customer base to the cloud. In the third quarter of this year, it plans to discontinue new server license sales in addition to increasing prices for on-premises products. Ironically, the company reported preliminary results for its most recent third quarter that indicate revenues of between $566 million to $572 million. That’s $85 million more than originally forecasted, because demand for on-premises products has increased in anticipation of their unavailability later this year.

In general, both Atlassian and JFrog are strong proponents of a best-of-breed approach to DevOps. JFrog, in its most recent quarter, reported $42.7 million in revenue, representing a 39% gain. Cloud revenue in that quarter grew 69% to $9.8 million, representing 23% of total revenue.

It’s unclear at what rate organizations are shifting to the cloud. The number of workloads moving into the cloud has certainly accelerated in the wake of the economic downturn brought on by the COVID-19 pandemic. However, the bulk of data continues to reside in on-premises environments, and many organizations, because of performance, security and compliance concerns, don’t have any immediate plans to migrate all their applications to the cloud.

Regardless of where DevOps platforms reside, there will always be a need to integrate them. It just may be easier to achieve that goal when all the tools that make up that workflow are running in the cloud.

April 29, 2021
IBM Unifies Cloud Services to Simplify App Dev

IBM announced today that an IBM Cloud Code Engine service that unifies the cloud platforms on which applications are built and deployed is now generally available.

Built on top of a serverless computing platform, IBM Cloud Code Engine is a managed service that unifies access to a platform-as-a-service (PaaS) environment, a container-as-a-service (CaaS) environment and batch workloads, that run on traditional virtual machines, to a single platform.

At the core of that managed service is an instance of Kubernetes running Knative middleware for invoking an open source serverless computing framework, the Istio service mesh and Tekton pipelines for building DevOps workflows.

Jason McGee, CTO and vice president for IBM Cloud Platform, said the goal is to eliminate the artificial constructs that developers are forced to navigate in the cloud today that can each trace their lineage to a different era of software development. The IBM Cloud Code Engine unifies the developer experience in a way that makes it simpler to build and deploy applications on the type of cloud service that best makes sense for a specific application workload, McGee said. Developers no longer need to configure code for a specific type of infrastructure; they can simply describe how they want source code or a container image to behave, and IBM Cloud Code Engine automates deployments accordingly.

The serverless computing framework that IBM Cloud Code Engine is built on also makes it possible for IBM to only charge organizations when code is actually running, versus requiring them to commit to a specific amount of infrastructure to run a set of virtual machines, McGee added. Charges are based on the memory and vCPU consumed and incoming HTTP calls. That approach will, over time, substantially reduce the total cost of cloud computing, said McGee.

It should also accelerate the rate at which applications are migrating to the cloud, added McGee. Today roughly 20% of application workloads run in the cloud. Getting the next 40% of workloads shifted into the cloud will require providing a simplified application developer experience, noted McGee.

The challenge organizations are wrestling with today is that they are deploying a mix of monolithic and microservices-based applications in the cloud that, to varying degrees, rely on batch-oriented and real-time platforms. IBM Cloud Code Engine represents an effort to provide a layer of abstraction over a wide range of cloud services that they can flexibly invoke via an event-driven platform, as required.

The DevOps implications of IBM Cloud Code Engine are potentially profound. DevOps teams today spend an inordinate amount of time provisioning cloud infrastructure on behalf of developers. IBM is now making a case for a platform that automates that process in few seconds. In effect, control over cloud infrastructure will shift even further left to application developers. DevOps teams, in theory, will spend more of their time optimizing cloud environments after an application has been deployed.

It’s not clear to what degree platforms such as IBM Cloud Code Engine might force cloud service providers to consolidate distinct cloud services they provide to developers today based on the type of application being built. However, it’s already apparent that the writing on the wall heralding that consolidation have now been indelibly inscribed.

April 28, 2021
Oracle Extends Capabilities of Enterprise Manager Platform

Oracle today announced it has updated its core management platform to provide capabilities that make it easier to manage a hybrid cloud computing environment spanning millions of endpoints.

The latest release of Oracle Enterprise Manager (EM) 13c, in addition to greater scalability, also provides support for dynamic groups, dynamic runbooks, automated workload analysis, monitoring templates, event compression and other capabilities that make it easier to manage IT operations at scale.

Oracle Enterprise Manager (EM) 13c Release 5 also extends the reach of the management platform further into the realm of packaged Oracle applications and integrated hardware and software platforms such as Oracle Exadata, Oracle Database Appliance (ODA), Zero Data Loss Recovery Appliance (ZDLRA) and Private Cloud Appliance (PCA).

Oracle has also updated the compliance framework it includes with Oracle Enterprise EM to support additional regulatory requirements and refreshed the user interface for the fleet management tool provided.

Finally, the company is adding a tool that makes it easier to copy data stored within Oracle EM 13c to the Oracle Cloud Infrastructure (OCI) service. Dubbed OCI bridge, this tool copies data to an OCI object store where it is accessed by OCI services such as logging analytics and operations insights.

Mughees Minhas, vice president of product management for enterprise and cloud manageability at Oracle, said as hybrid cloud computing continues to evolve, the need for a single management platform that spans infrastructure, databases and applications is becoming more apparent.

Minhas said Oracle EM 13c is part of larger observability initiative that Oracle has embraced to provide more context across disparate services in a way that reduces the total number of tools an IT team needs to deploy and master. That effort complements a series of autonomous computing initiatives Oracle has previously launched that eliminates the need for database administrators (DBAs) to manage lower level systems administration tasks such as performance tuning. In general, Oracle is making a case for an IT world where platforms are co-managed by Oracle and internal IT teams that are focused on higher-level tasks.

As IT environments become more distributed it’s clear IT is becoming more complex to manage. The issue that IT teams need to come to terms with is to what degree can they automate management tasks that today conspire to limit the size of the IT environment any given IT team can effectively manage. DevOps teams, of course, have been ruthlessly automating application development and deployment tasks for years. That philosophy is now being extended to include a broader range of IT operations tasks being automated by vendors themselves.

Each IT team will ultimately need to decide just how many automation platforms it requires. In many cases, IT teams are now struggling to unite various islands of automation that have now emerged within their organization. Regardless of approach, however, rote tasks that once consumed hours, sometimes days to complete, are now no longer required which, theoretically at least, should leave more time to focus on more complex challenges that are getting thornier by the day.

April 27, 2021
Red Hat Extends Reach and Scope of Insights Analytics Service

During its online Red Hat Summit event, Red Hat today announced it has extended the Red Hat Insights predictive analytics cloud platform for managing IT to now include support for editions of Red Hat OpenShift based on Kubernetes and the Red Hat Ansible Automation Platform.

In addition, Red Hat has extended Red Hat Insights for Red Hat Enterprise Linux (RHEL) to include the ability to prioritize security alerts, streamline notifications and track Red Hat subscription consumption.

In total, since launching Red Hat Insights in 2019, Red Hat claims there are now more than 600,000 RHEL hosts analyzed per day.

Joe Fitzgerald, vice president and general manager for the management business unit at Red Hat, said Red Hat Insights provides IT teams with the equivalent of a co-pilot for managing IT environments. In general, advances in automation and artificial intelligence (AI) are making it easier to manage complex IT environments at scale, noted Fitzgerald. However, it’s not likely IT environments will be automated to the point where lights-out management without human intervention is likely to be achieved any time soon, added Fitzgerald.

However, it’s also becoming apparent that it’s not possible for IT teams to manage complex IT environments without help in the form of advanced analytics tools. In fact, while many IT professionals are leery of automation tools because of the perceived threat to their jobs, it’s also becoming apparent that IT teams will not be able to manage modern IT environments without these tools. Organizations can’t afford to hire small armies of IT personnel. In addition, finding and retaining IT professionals that have, for example, Red Hat OpenShift skills remains a significant challenge.

Red Hat Insights provides IT teams with additional levels of context required to manage these environments that goes beyond simple monitoring, noted Fitzgerald. That’s critical, as the IT environment becomes more extended in the age of hybrid cloud and the rate at which platforms are updated steadily increases, added Fitzgerald. Platforms such as Red Hat OpenShift, for example, are now typically updated every three to four months.

DevOps, of course, has always been about ruthlessly applying automation whenever possible. As analytics applications become more robust, IT teams gain the visibility required to automate a wider range of complex tasks, noted Fitzgerald. In fact, in the absence of that visibility, automation can be a dangerous thing when mistakes caused by a lack of visibility and insight are made, added Fitzgerald.

In the longer term, Red Hat expects to see continued convergence of job functions and roles as IT teams become more cross-functional, said Fitzgerald. Platforms such as Red Hat Insights will provide a single console around which these teams can collaborate, added Fitzgerald.

Going forward, there won’t be a handful of administrators with augmented capabilities. Rather, IT specialists that have a particular set of skills will be able to collaborate more easily in a way that both creates a better outcome and ultimately keeps a lid on the total cost of IT.

April 27, 2021
WhiteSource Acquires Diffend to Secure Open Source Supply Chains

WhiteSource this week announced it has acquired Diffend as part of an expended effort to discover malware that has been deliberately injected into open source software by a contributor acting in bad faith.

Company CEO Rami Sass said cybercriminals are increasingly trying to compromise software supply chains that today depend heavily on open source projects. The Diffend platform surfaces anomalous contributor behavior that would be indicative of someone trying to compromise the integrity of a project, said Sass.

Previously, WhiteSource provided a tool that would discover malware that had been inadvertently included in open source software. WhiteSource now plans to add the Diffend tools, now known as WhiteSource Diffend, for free to a portfolio of security tools that many organizations have already incorporated into DevSecOps workflows. Earlier this month, the company raised an additional $75 million in financing that, in part, was used to fund this acquisition.

As cybercriminals begin to target software supply chains, many of them are taking aim at open source software that is likely to be adopted by a broad spectrum of organizations, noted Sass. The challenge is that bad actors have become adept at embedding malware in software components in ways that are difficult to detect, he said. However, spikes in activity from, for example, a new contributor to the project might warrant additional investigation, Saas added.

These type of attacks, unfortunately, will require the maintainers of open source software to vet more closely who is allowed to contribute to the project, added SaaS. New contributors that might have once been greeted with open arms need to now be initially met with a modicum of paranoia, Saas said.

That level of suspicion will be considerably higher if that contributor is located in a country that has a reputation for trying to compromise the security of both adversaries and companies that have intellectual property they might want to surreptitiously acquire.

In the wake of some recent high-profile breaches involving software supply chain compromises, organizations are revisiting their application development processes. Cybersecurity teams are now asking developers to vet any external code that is incorporated within an application. Most applications regularly incorporate both open source and commercial components that developers assume have been vetted for malware when, in most cases, they have not. The Diffend platform, for example, aided in the detecting of 60 suspicious packages found in Rubygems, an open source platform that makes it easier to package software built using Ruby programming tools.

It’s unclear how increased inspection of software components may impact application developer productivity. However, given how dependent organizations are on software today, the discovery of malware downstream that compromises the security of the application is potentially catastrophic.

Sass said it’s doubtful these security concerns will lead to decreased reliance on open source software in general. There is no real alternative for efficiently driving software innovation, he said. The challenge now is finding a way to make sure all that innovation continues to occur as securely as possible.

April 23, 2021
ServiceNow Shifts to Single Unified Agent

ServiceNow today unveiled an Agent Client Collector (ACC) that makes it possible for IT teams to capture data from software, hardware and cloud infrastructure.

Jeff Hausman, vice president and general manager for IT operations management at ServiceNow, said this unified agent will enable IT teams to reduce the number of agents they would otherwise have to deploy to collect the data required to monitor IT environments.

IT teams will also be able to employ incident management tools that can view that data in a way that eliminates the need to install any remote desktop software, Hausman noted. At a time when many employees will be splitting their time between working from home and the office, that approach reduces the level of IT service management (ITSM) friction that many IT teams today regularly encounter, added Hausman.

ACC surfaces both configuration and performance data in real-time to provide IT teams with greater visibility. That data can then be used to drive a variety of workflows and playbooks that trigger automated incident responses.

ServiceNow will employ ACC both within its ITSM platforms and IT operations management (ITOM), hardware asset management (HAM), software asset management (SAM), and security operations (SecOps) tools.

Hausman said ServiceNow will employ ACC alongside agentless tools for managing IT environments as part of an effort to strike a balance between the amount of software that needs to be deployed and the capabilities that agent software enables. Ultimately, ServiceNow will also open up ACC to third-party tools that offer complementary capabilities, he added.

More than a few IT organizations are suffering today from a phenomenon known as agent fatigue. Each new tool added to the IT arsenal often requires agent software to be installed within a device, application, server or cloud service. The need to reduce the amount of agent software has given rise to agentless approaches to managing IT resources, but the tradeoff is that, in the absence of an agent, the types of data and capabilities that can be enabled tend to be more limited.

The market research firm International Data Corp. (IDC) is predicting that 75% of Global 2000 IT organizations will adopt automated operations practices by 2023. A major driver of that increased reliance on automation has been, of course, the COVID-19 pandemic. Not only are organizations making greater use of cloud infrastructure, but application users are not often conveniently located behind a firewall in a corporate office. For the last year, IT teams have been tasked with supporting a largely remote workforce. As more of those employees are vaccinated in the weeks ahead, a lot more of them will be returning to the office. However, it’s unlikely most employees will be working in an office full-time even after the COVID-19 pandemic subsides.

Regardless of how IT is managed, the overall IT environment will continue to become more complex. As such, it’s now more a question of when rather than if organizations will need to revisit how IT gets managed across what has become a highly distributed environment.

April 22, 2021
Survey Shows Acceleration of Centralized IT Management

An OpsRamp survey published this week suggests large enterprises are looking to finally unify IT management at at time when it is becoming increasingly complex.

OpsRamp, a provider of an IT management platform based on machine learning algorithms, polled 132 IT operations directors working for organizations in the U.S. with more than 500 employees that spend more than $5 million a year on IT.

According to the results, the survey found nearly 73% of respondents plan to roll out a digital operations management platform in 2021. That platform will, hopefully, enable IT teams to unify hybrid cloud computing environments made up of monolithic and microservices-based applications via a single console. Another 21%of respondents expressed interest in such a platform, if budgetary constraints allowed.

More than half (51%) also noted they expect to employ automation and AIOps (51%) in the form of machine learning algorithms and process automation to reliably cut down on the number of alerts being generated, identify the root cause of issues and eliminate repetitive manual tasks.

The two main goals identified in the survey are to enable greater agility and resolve issues faster (46%) and reduce costs by consolidating tools (41%).

While the rise of cloud computing has made IT more agile, each cloud service that is added to the IT firmament tends to increase the total cost of IT. Each IT platform in use today requires a dedicated team to operate, which conspires to increase both the number of tools required and the overall size of the IT staff required to master them.

In the wake of the economic downturn during the COVID-19 pandemic, the amount of pressure being applied to reduce those costs has increased significantly. Security and compliance concerns are also starting to push organizations toward centralizing the management of IT as much as possible. The OpsRamp survey notes that platform security (59%) is the most critical attribute of a next-generation IT platform, followed by hybrid infrastructure management capabilities (52%) and flexible pricing (37%).

Deepak Jannu, senior director for product marketing at OpsRamp, said achieving those goals across what has become an extended enterprise requires a platform that has the ability to first capture telemetry data in real-time and then aggregate that data in way that enables artificial intelligence (AI) models to learn how the IT environment actually operates.

Armed with that data, it then becomes possible to employ AI to both troubleshoot IT issues more easily and surface recommendations that address capacity utilization, noted Jannu.

It may be a while before AI-enabled IT management platforms are commonplace in the enterprise. However, it’s also apparent a number of factors are driving IT leaders to reevaluate their existing platforms as IT environments become increasingly more complex.

Regardless of what platform an organization eventually opts to standardize on, the rate at which IT management tasks are being automated is only going to increase as machine learning algorithms become more familiar with the IT environment in which they are deployed. That doesn’t necessarily mean those algorithms will remove the need for IT administrators and DevOps teams, however. It does mean that the tasks the individuals on IT teams are focused on will, hopefully, provide a lot more value to the business.

April 21, 2021
Applause Delivers Testing Integration Tool

Applause today made a bi-directional integration capability that simplifies requesting application code tests of, dubbed Applause In-Sprint Testing, generally available.

Kristin Simonini, vice president of product for Applause, said application owners will be able to, for example, use a Jira project management application to create a ticket that requests a specific piece of code be tested either by a member of dedicated testing team or by a developer that has assumed greater responsibility for application testing within the context of a DevOps workflow.
Alternatively, that request could be sent to a tester that is a member of uTest, an online community of professional testers that Applause oversees.

The company also published the results of a global survey of 1,800 quality assurance (QA), product, engineering and DevOps professionals that found 44% of development teams that have shifted application testing left are spending a full workday every week on application testing. More than half the respondents (52%) noted that amount of time spent on testing is impacting developer productivity.

On the plus side, a full 88% of respondents that release code multiple times per month said their organizations now test features as they are developed versus waiting until the end of application development process, the survey also found.

The major benefits of shifting testing left cited by respondents are reducing the number of bugs released into production environments (57%), reducing the cost of late-stage bug fixes (48%), and reducing the need for hot-fixes (39%).

The top two barriers to shifting responsibility for testing left toward developers is they are too busy coding (45%) and that development and quality assurance (QA) efforts remain siloed (37%). Nearly half of developers (44%) said they have issues with context switching as they shift between coding and testing tasks.

Simonini said Applause In-Sprint Testing will make it easier for application owners to decide when they want to make use of a professional tester versus having a developer run a test. The Applause Product Excellence Platform then enables IT organizations to leverage a software-as-a-service (SaaS) platform to record a series of test case scenarios that can be automatically converted into an automation script without anyone having to write code.

The overall goal is to simplify testing at a time when the number of applications being built has accelerated in part because of the increased focus on digital business transformation that occurred in the wake of the economic downturn brought on by the COVID-19 pandemic. As organizations realize how dependent they have become on those applications to differentiate themselves, the focus on quality assurance naturally intensifies, noted Simonini.

There’s no doubt more organizations are testing with greater frequency. The efforts of developers that previously tended to address large numbers of bugs as part of a series of application updates after deployment in production are now being frowned upon. Organizations realize their applications only get one chance to make a first impression with end customers. As a result, the level of attention to detail being applied to application testing has, for better or worse, never been greater.

April 21, 2021
Redis Labs Extends Reach of In-Memory Database

At its online RedisConf 2021 event, Redis Labs today detailed how the company’s in-memory database will be employed to drive real-time applications that are at the core of most digital business transformation initiatives.

Yiftach Shoolman, Redis Labs CTO and co-founder, said there are four initiatives at the core of the Redis Labs effort to replace legacy databases that organizations have historically employed to drive batch-oriented application processes.

RedisRaft, which will become available with release 7.0 of the Redis database in the third quarter, provides a module based on the Raft consensus algorithm that enable multiple Redis servers to be consumed by an application as if they were one single, fault-tolerant, logical cluster. That capability will provide IT teams with the ability to distribute Redis servers closer to the point where data is being consumed by a distributed application without incurring any conflicts between databases, said Shoolman.

At the same time, Redis is extending its Active-Active technology to enable integrated data models to be deployed in a way that allows distributed applications to run as close as possible to the point where data is being created and consumed.

Finally, RediSearch is being updated to include support for indexing capabilities in JSON applications using a nested document model, while a RedisAI capability will add an inference engine for artificial intelligence (AI) applications that can be employed as a feature store through which the deployment of AI models within applications can be managed. That approach also promises to significantly increase the overall performance of AI applications, noted Shoolman.

Historically, the Redis in-memory database has been best known for the caching capabilities it provides developers. However, Shoolman noted 66% of organizations that employ the Redis database are using it for additional use cases. As microservices that are often configured with their own database become more prevalent, the adoption of an in-memory database platform should only increase, added Shoolman.

Many of those microservices are being employed within the context of a digital business transformation project. The issue that organizations are coming to terms with is most of those processes need to run in near real-time. That requirement will eventually push more organizations toward deploying a database based on a distributed database running in-memory that appears as one logical entity to an application, said Shoolman.

At its core, Redis a data store that supports structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams. Among other capabilities, it includes support for built-in replication, Lua scripting, transactions and varying levels of persistence. The company claims the core Redis datastore has been downloaded 1.5 million times in the last nine years.

On top of that installed base, Redis Labs then makes available tools for deploying and managing Redis within large-scale application environments. Most recently, Redis Labs raised an additional $100 million round of financing to bring its valuation to above $2 billion. The company now claims to have more than 8,000 paying customers, with a 54% compound annual growth rate in sales for the past three years.

It’s hard to say to what degree Redis data stores might supplant legacy database platforms. However, the one thing that is certain is there are lot more databases running in memory that, in many cases, obviate the need for a traditional relational database.

April 20, 2021