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Sustainable IT and Data Innovation: Driving the Future of DevOps

The worlds of sustainable IT and data innovation are converging, and two upcoming events are set to showcase the latest developments in these critical areas of sustainable IT and data innovation. The SustainableIT Impact Awards & Symposium and the DevOps + Data Impact 2024 promise to bring together industry leaders, experts, and practitioners to explore how technology can drive positive change in both business and society.

Inaugural Impact Summit & Awards, SustainableIT.org

Sustainability Takes Center Stage

Sustainable IT has become a key focus for organizations across the globe, as the environmental impact of technology comes under increasing scrutiny. The SustainableIT Impact Awards & Symposium will be held in Austin, Texas. It aims to celebrate the institutions and individuals who are leading the way in this field. The event, organized by the nonprofit SustainableIT.org, will feature a range of awards, including the Environmental Award, which recognizes success in reducing energy consumption and emissions across technology infrastructure, and the Governance Award, which celebrates institutions that have woven sustainability into their decision-making processes.

Meanwhile, the DevOps + Data Impact 2024, presented by Perforce and Delphix, also in Austin, will dive deep into the world of data management and its role in driving innovation. As enterprises grapple with the challenges of managing and leveraging vast amounts of data, the conference promises to offer valuable insights and solutions. Attendees can expect to learn about the latest trends in data analytics, security, and compliance. Plus they will gain insights on strategies for optimizing data management to drive business success.

Perforce’s Acquisition of Delphix: Driving Sustainable Data Management

Perforce’s recent acquisition of Delphix, a leading provider of DataOps solutions, reflects the growing importance of data management in the DevOps landscape. This strategic move aims to help customers automate and accelerate their DevOps pipelines while promoting sustainable IT practices. As Perforce CEO Jim Cassens noted, “Data is at the heart of how enterprises operate today and essential for successful software development, but accessing and managing that data is extremely challenging. Many teams do not have rapid access to solid, high-quality test data.”

By integrating Delphix’s capabilities, Perforce seeks to address these challenges and enable more efficient and sustainable data management practices. As Cassens stated in a blog post announcing the acquisition, “Another unique ability of the Delphix platform is how it virtualizes data and ultimately reduces storage footprints, which is good news for sustainability and operational costs.”

Bridging Sustainable IT and Data Innovation

The convergence of these two events points to a broader trend in the DevOps world: the need to balance sustainable IT and data innovation. Organizations are increasingly recognizing that sustainability efforts can drive efficiency and innovation. Accordingly, robust data management can support environmental goals.

As the DevOps landscape continues to evolve, look for more initiatives that emphasize balance with AI-driven energy management in data centers, sustainable IT and software development practices, and circular economy approaches to IT hardware. Certainly, the upcoming events in Austin serve as a barometer for these trends, offering a glimpse into how industry leaders are navigating the complex intersection of technology, data, and sustainability. By attending these events and engaging with the insights they provide, DevOps teams can position themselves at the forefront of sustainable innovation, driving both business success and positive environmental impact.

September 2, 2024
Five Great DevOps Job Opportunities

DevOps.com is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted as part of an effort to better serve our audience.

Our goal in these challenging economic times is to make it just that much easier for DevOps professionals to advance their careers.

Of course, the pool of available DevOps talent is still relatively constrained so when one DevOps professional takes on a new role it tends to create an opportunity for others.

The five job postings shared this week are selected based on the company looking to hire, the vertical industry segment and naturally, the pay scale being offered.

We’re also committed to providing additional insights into the state of the DevOps job market. In the meantime, for your consideration.

SimplyHired.com

Dimensional Analytics
Chantilly, VA
DevOps Engineer
$200,000 to $265,000

LinkedIn

Spotify
Remote
Site Reliability Engineer (SRE)
$122,700 to $175,300

CareerBuilder.com

McAfee
Remote
Senior AWS Cloud and DevOps Architect
$120,650 to $203,150

Indeed.com

Workday
Atlanta
DevOps Security Engineer III
$117,800 to $207,600

Dice.com

Raytheon
Aurora, CO
Senior Software DevOps Engineer
$77,000 to $163,000

September 2, 2024
DevOps Must Learn From CrowdStrike’s Outage
The CrowdStrike outage on July 19, 2024, is a stark reminder of DevOps practices’ critical role in deploying updates to maintain the security and reliability of applications and systems. While the underlying software defect was the immediate cause, the broader issue lies in the deployment process that allowed a severe flaw to impact a global customer base.

Key Takeaway: To maintain trust and reliability in today’s complex software, security, cloud and data center ecosystem, we must prioritize robust, measured deployment strategies.

The ability to rapidly deploy software updates across large, diverse environments is necessary for many software offerings. Updates can have unintended and, rarely, catastrophic consequences if done improperly or without diligent governance. The CrowdStrike incident highlights the importance of adopting more sophisticated deployment strategies—such as staggered, A-B, canary and phased rollouts—to minimize the blast radius of any potential defects. By initially releasing updates to a smaller subset of systems, organizations can validate changes in real-world conditions, catching issues before they affect the entire user base. Then, the update can be released in stages to increase the number of customers. This approach significantly reduces the risk of widespread disruptions and ensures that problems are contained and addressed quickly.

Additional Resources
- Research Note: The CrowdStrike Outage – A Detailed Post-Mortem
- Research Note: CrowdStrike IT Outage: Critical Global Impact and Implications for Cybersecurity
Let’s move beyond this single CrowdStrike incident and focus on the lessons we need to learn to avoid repeating them in the future. As software delivery becomes faster and more automated, the need for meticulous, well-orchestrated deployment processes has never been greater. It’s not just about preventing the next outage; it’s about building a culture of reliability and accountability in every step and layer of the software supply chain. The urgency of this need cannot be overstated.

Customers of software vendors bear a crucial responsibility in ensuring their systems remain secure and reliable. They should not rely on automatic updates without oversight, as doing so can leave their environments vulnerable to unforeseen issues. Organizations need to implement their own vetting and validation processes, testing updates in controlled environments before widespread deployment. This added layer of scrutiny helps catch potential problems early and prevents disruptions from unquestioningly trusting every update. In this way, customers play an active role in maintaining the integrity of their systems and minimizing risks.

This is our call to action: To maintain trust and reliability in today’s complex software, security, cloud and data center ecosystem, we must prioritize robust, measured deployment strategies.

Mitch Ashley is Chief Technology Advisor with The Futurum Group and CTO of Techstrong Group’s tech media platforms covering DevOps, cybersecurity, AI, cloud native, cloud infrastructure, platforms and ITSM.

Mitch’s analyst research is available on FuturumGroup.com and TechstrongResearch.com.
September 1, 2024
Operations as Code: Transforming Operational Excellence
The push toward digital transformation and cloud-native infrastructure is inevitable. This shift brings the need to manage operations with the same rigor and automation we apply to infrastructure or security. Many organizations have embraced the ideas of everything in a pipeline and all things as code. While platform engineering and other teams have created answers for building and delivering applications and the necessary frameworks in which to run them, the actual operations of service delivery are often disjointed and purely reactive.

Enter operations as code.

By leveraging tools such as Terraform with automation and CI/CD pipelines, site reliability engineering (SRE), DevOps and DevSecOps teams can standardize and automate operational tasks, ensuring consistency, efficiency and reliability.

Operations as code extends the principles of infrastructure as code (IaC) to operational procedures. It involves defining, managing and executing operational tasks — such as defining escalation policies, defining runbooks and executing playbooks — using code and automation tools. This approach ensures that operational practices are repeatable, version-controlled and can be executed with minimal human intervention.

Avoiding Bottlenecks

One of the greatest benefits of the operations as code approach is the ability to remove the dependency on centralized teams. As the need for speed across DevOps practices increases, these teams cannot be beholden to centralized ITSM or other teams for their needs to integrate new monitoring, enrich events or create new runbooks.

Similarly, centralized teams devoting expensive, specialized skills on monitoring integrations, event management, enrichment and automation that can be managed via operations as code makes little economic sense. These teams, especially in large organizations, are already stretched thin and the backlog of work grows daily. Leveraging Terraform or other mechanisms to achieve the same goals while delivering better outcomes makes more sense for all teams working together.

Leveraging Pipelines and Terraform for Operations

Terraform, traditionally used for IaC, has become the lingua franca of DevOps. By writing Terraform configurations, teams can automate the provisioning and management of not only infrastructure but also the operational workflows that ensure operational excellence. For instance, Terraform configurations can define tasks such as service definitions, configuring users, teams and roles, defining escalation policies and schedules, defining event correlation and orchestration and defining automation such as runbooks and automated diagnostics.

CI/CD pipelines play a crucial role in operations as code. By integrating operational tasks into CI/CD pipelines, you can ensure that changes are tested, reviewed and deployed in a controlled and automated manner.

Quality gates are traditionally used for code reviews, automated testing, security checks, etc. For operations as code, they can be leveraged for standardization by ensuring consistency of core functionality such as service standards, tiers of escalation policies, minimum requirements for runbooks, etc. Performing compliance checks to ensure operational changes comply with internal policies and external regulations. And eventually, they can be used for scoring applications for operational readiness.

Benefits of Operations as Code

Organizations that deploy operations as code will see several benefits, many with immediate return on investment (ROI).

Toil reduction is critical. Too much time is spent in ‘ClickOps’, and by shifting from manual configurations, more time is freed up to grow automation and free up resources for more valuable work. You can also reduce operational risk by ensuring the traceability of changes to configurations, version control and templates that reduce the risk of error. Similarly, you can operationalize governance and compliance by leveraging parsers, quality gates and approved templates, while leadership can define acceptable minimum standards and expected outcomes.

Operational excellence is improved by reducing the frequency, severity and duration of outages by ensuring repeatable outcomes and reduced errors. You can shift away from tribal knowledge by giving senior people a simplified, repeatable method to record their innate knowledge for reuse and creating a context for junior staff.

Developer experience is improved by reducing the ramp time of new team members, allowing them to focus more on high-value work and building capabilities, while putting in less time looking for ‘how to’ or escalating to experts. Most importantly, you can start a shift from run to build by reducing the amount of time in keeping the lights on and chasing break-fix work, while the senior staff can focus on reducing tech debt (or mining tech wealth if you are optimistic) to deliver great customer experiences.

Getting Started

Successfully rolling out operations as code involves several key steps:
- Firstly, you must define success. How are you going to measure the efficacy of your operations? Think beyond the mean time to repair (MTTR). What about the cost of keeping the lights on or reducing the time and cost of break-fix work? How can you better attack tech debt?
- Next, assess current operations and identify the initial areas that can benefit from automation and templates. What can you immediately de-risk or outcomes could you influence with standardizing operations?
- Then, ensure you have the appropriate tools that fit your environment and architectural goals and that your teams are trained in those tools and associated best practices. You will want to establish a center of excellence by building teams of enthusiasts and experts who can help with Q&A, become keepers of the templates and help build continuous automation and orchestration improvements.
- Lastly, focus on incremental implementation starting with simple but impactful areas, and then build using continuous improvement to regularly review and improve your processes based on feedback and metrics.
What’s Next?

Operations as code represents the next frontier in IT management, offering the promise of consistency, efficiency and reliability in operational tasks. By leveraging Terraform, CI/CD pipelines and robust tools, you can lead your teams in adopting this transformative approach. While challenges exist, they are surmountable with careful planning, execution and continuous improvement. Operations as code can be a cornerstone of operational excellence allowing your teams to help move from a world of toil and break-fix to building the capabilities that will help you win in the marketplace, better serve your teams and most importantly, your customers.
August 31, 2024
AWS Cloud Migration Strategy
Cloud migration is moving data, applications or other services to a cloud computing environment from an on-prem data center. Migrating your project means moving your data from the on-premises data center to the cloud. In this case, the cloud is the virtualization used over a data center to make the functionalities more flexible. Many companies like GoDaddy, Expedia, Netflix, startups, etc., have recently moved their business to the cloud. Migration is a big task and AWS facilitates migration in phases.

Need for Migration

Business is no easy task when handling situations like security, scaling up or down, etc. Let’s look at a few scenarios where AWS Migration could be a better resort.
1. More users coming in amid high-performance
2. Faster implementation and deployment needs
3. Expensive to manage a growing database
4. Datacenter mishap went down
We can conclude that the following are key reasons to migrate to the cloud:
- Zero capital cost on infrastructure
- Security
- Scalable (vertically and horizontally)
- Productivity
- Pay what you use
- Easy to manage services
- Reduced operational costs
If you migrate to the cloud, the abovementioned problems will be handled automatically. Let’s move further and understand what migration is.

Phases of AWS Migration

AWS Cloud Migration is a step-by-step process that consists of planning, preparation and discovery, migration and optimization. However, it is more complex as the process involves different phases. Let me now talk about the various phases of migration.

Phase 1: Migration Preparation and Business Planning

In this phase, you identify the need, objective and benefits of cloud migration. You perform a POC and verify the outcome to compare the performance and costs. There are also times when you need not move your entire business to the cloud. This is where segregation is important. You need to identify the applications which can be migrated and those which cannot. This is what the first phase is all about.

Phase 2: Assessment — Choosing Your Migration Method (Discovery and Analysis & Assessment)

The first step is to identify the assets that need to be migrated to the cloud — gather the details such as the number of servers to migrate, road map to migration, record business-critical activities, server size, memory utilization, CPU utilization, environment type and data. You can use the ‘AWS Application Discovery Service’ to check the technical details by installing it in your server. Depending on the data, AWS provides different ways to migrate your application, e.g., AWS Snowball, AWS Snowmobile, AWS Direct Connect, etc. Also, assess the cost of renting servers, storage, network and support. Prepare the checklist for regulatory and compliance assessment and perform the security assessment.

Phase 3: Proof of Concept (POC) for AWS Storage/Designing

Once you know how and what you are migrating, next, you must plan your delivery priorities and design the AWS Cloud Migration process. You will identify the dependencies (upstream and downstream components). Define the organization or account strategy for users, VPC strategy and what cloud pattern it will be (hybrid/fully cloud) and other parameters like security.

Phase 4: Migration to AWS

Now that you have all the prerequisites such as the blueprint, migration tools, a list of assignments, backups, and its synchronization with your on-premises data repositories, you can finally migrate your project/application to AWS Cloud. Once you have migrated your project to the cloud, reliability and durability are the added benefits you get. For application code/server migration use AWS Server Migration Service, for database, you can use AWS Database Migration Service and other import/export AWS services.

Phase 5: Enterprise Cloud Operations (Operate and Optimize)

At this point, you have already migrated to AWS and it will bring updates that you would need to incorporate in your existing architecture. Optimize your architecture, have your support team ready to look for the new features and cost optimization, improve the applications using serverless, use AWS monitoring and logging services and implement CloudFormation and DevOps.

Application Migration Strategies ‘The 6 Rs’

The complexity of migrating existing applications varies, depending on the architecture, Amazon came up with different strategies which they commonly termed as 6 R’s. Let’s look into each of them:

Benefits of AWS Migration
1. Elasticity: Adding and removing capacity whenever it is needed is the greatest benefit of
2. Disaster Recovery: With 95% guaranteed uptime, businesses can be confident knowing that their data will always be available.
3. Enhanced Cost Management: The IaaS platform provides two major First, an IaaS such as Amazon Web Services is available as a monthly service. Second, it eliminates the need to continue to purchase and maintain physical hardware.
Services for AWS Migration

Out of the many tools provided by Amazon to automate data migration, I will be talking about the more commonly used ones.

AWS Migration Hub: AWS provides a single location for tracking the migration process. Migration Hub gives you the freedom to choose your migration partner and tools that fit your needs.

AWS Server Migration Service (SMS): AWS SMS is an agentless service that helps migrate loads of on-premises workload to AWS easily and faster. It allows you to automate migration and track the replication of the server. It makes coordinating with your large-scale-server migration easier.

Amazon S3 Transfer Acceleration: This makes the transfer of files over long range to the AWS S3 bucket faster and more secure.

AWS Snowball: It is a petabyte-scale data transfer solution that uses secure devices to transfer a large amount of data in and out of AWS.

AWS Snowmobile: It is an exabyte-scale data transfer solution to move an extremely large amount of data to AWS. Snowmobile makes the transfer of massive volumes of data easier.

Amazon Kinesis Firehose: It is the easiest out of all the methods. It can capture and automatically load streaming data into Amazon S3. You can analyze real-time data to get timely insights of the migration.

Now that you know everything about AWS, and AWS Migration, let me show you a use case where you will be migrating a Virtual OS from my local machine to AWS Cloud.

AWS Data Migration

Data can be moved from on-prem to AWS Datacenter using the following means:
- Amazon S3 Transfer Acceleration — for faster transfer over the internet change the endpoint you use with your S3 bucket and acceleration is automatically applied.
- AWS Snowball — a petabyte-scale data transport solution that uses secure appliances to transfer large amounts of data into and out of AWS.
- AWS Direct Connect — you establish a dedicated network connection between your network and one of the AWS Direct Connect locations for transfer.
Demo: Implementing Migration Using the Import/ Export Method

You will be migrating an on-premises Virtual OS running on VMWare to AWS using the import/export (AWS Direct Connect) method.

Pre-requisite
Create a .vmdk export file for Ubuntu 14.04.
1. Download and configure AWS
1. Create an IAM
IAM – User —Add User —AccessType (Programmatic Access) —Attach Admin Access Policy —Create User.
1. Create an S3 bucket and add a file (image file of the OS).
2. You can upload the file using AWS CLI aws s3 cp “source path” <s3 bucket>
3. Once the file is uploaded, create an AMI for the imported image
Aws ec2 import-image –description “AWS Linux” –disk-containers file://containers.json
1. Now your AMI is available, and you can see it under AMI in EC2 and run it as and when
Thus, we have successfully migrated a virtual OS on AWS.

By now you should have a fair idea about the AWS Cloud Migration strategy and the process, tools and transfer mechanisms available.
August 31, 2024
Developers’ Enthusiasm for Generative AI is Growing: Survey

Developers are increasingly positive about generative AI’s effects on their jobs and their companies in general, a change in a community that in the past seemed to have feared it, according to a report released this week by cloud API developer Kong.

In addition, they say APIs will play an increasingly large role in the ongoing development of AI, with the integration with AI being the most critical aspect of API management over the next one to two years.

“For businesses, integrating AI into API management is crucial for automating and optimizing operations, enhancing security, and offering more personalized user experiences,” wrote the authors of Kong’s “API Impact Report 2024.” “It can allow for real-time anomaly detection, dynamic resource adjustment for optimal performance, and innovative service development.”

In a survey of 747 IT professionals and business leaders, 92% of respondents said that AI is a priority for their businesses and 83% said that AI investments in their organizations have opened up opportunities for new products or services over the past year.

That said, a trend toward users bypassing their organizations’ policies around AI use is putting pressure on companies to put in place tools like AI gateways and data loss prevention (DLP) solutions to ensure data governance and regulatory compliance, particularly as governments are increasingly putting new laws in place to make the use and innovation of generative AI safer, according to Kong.

AI Use Guidelines are Important

The report’s authors noted that organizations and individuals are adopting AI at a much faster pace than they did with previous technological breakthroughs, “which means organizations need to move faster than ever to keep on top of the wave of AI innovation.” About 80% of developers surveyed said their organizations have AI usage guidelines or restrictions, with about 20% having none in place. About 2% said their organizations ban generative AI tools outright.

About 60% of respondents said they find ways of getting around restrictions to access the AI tools they need. However, data privacy, security, and governance also top the list – at almost 60% – of challenges faced in integrating AI services with existing microservice infrastructures.

“We’ve reached the moment where AI adoption is imperative; however, doing so strategically will be the ultimate marker of long-term success,” said Marco Palladino, Kong’s co-founder and CTO. “Our report highlights the need for infrastructure underneath AI applications that provides strong governance while enhancing AI performance.”

Warming Up to Generative AI

The company’s report echoes what other vendors have found when it comes to developers and AI. A survey late last year by Kobiton found that most mobile app developers and testers are using generative AI tools for a range of tasks and to help address challenges in developer and QA operations. In addition, they’re using the technology when they have limited financial resources or not enough skilled programmers.

In April, Docker said in a report that software engineers are increasingly relying on AI to build their applications, with use cases ranging from coding and documentation to research, troubleshooting and debugging.

Similarly, Kong’s survey found developers are warming up to generative AI, with 60% saying they are passionate about working with the fast-emerging technology and 57% saying it will make their jobs easier.

However, others are still worried about it, with 35% saying that AI adoption is moving too fast. There also is the ongoing worry about the future, with 18% believing the use of AI tools will lead to layoffs at their companies. Almost one in 10 said they don’t want to work with AI, with some believing that AI will undervalue their work or increase their workloads.

“Zooming out from personal outlook to their view on business impact, half of those surveyed say AI will enhance productivity and innovation,” the authors wrote. “26% say AI will create new positions or opportunities in their organizations.”

APIs to Take a Central Role

APIs will become increasingly important in the development and use of AI, according to Kong. The company noted that APIs in general are widely used, with 85% of Fortune 100s using them as a core part of their IT operations and almost half of developers and managers saying their companies need to be more aware of the business value APIs deliver.

They’ll also play a central role in AI, with the report’s authors writing that “APIs enable communication between humans and AI systems — as well as AI systems and other digital tools. APIs serve as the hands, eyes and ears of AI. And as AI usage increases, so will the number of APIs that enable them.”

They pointed to a Gartner prediction that by 2026, more than 30% of the increase in demand for APIs will come from AI and tools using large language models (LLMs). Beyond that, Kong predicts the value of APIs to enable AI will grow 170% by 2030.

In that same timeframe, Kong’s research says that the economic impact of APIs in the United States will reach $3.4 trillion, with the global impact hitting $17.3 trillion. Leaning on data from the International Monetary Fund on projected worldwide GDP growth and the global digital economy, the economic impact of APIs should increase from 12.7% of global GDP this year to 14% in 2030.

“[A] simple back-of-the-napkin math paints a picture of why an API strategy is so essential for organizations today: In a short time, the consumers of our websites or digital products are more likely to be AI than human,” the authors wrote. “Whether we’re using AI, training AI or having AI interact with APIs to perform operations, an API is involved. That’s why controlling the usage of AI at the interface level is an API problem.”

August 30, 2024
Broadcom Adds On-Premises Edition of Project Management Application

Broadcom today at the VMware Explore 2024 conference added an on-premises edition of its Rally project management application for managing software engineering projects.

Jean-Louis Vignaud, head of ValueOps for the Agile Operations Division of Broadcom, said Rally Anywhere provides DevOps Teams with an alternative to the software-as-a-service (SaaS) edition of the platform that gives them more control over how their data is stored.

That’s a critical option for organizations operating in heavily regulated industries or any organization that is concerned about ransomware attacks that are increasingly being aimed at providers of SaaS applications, he added.

Broadcom is also looking to provide an alternative option to organizations that have been told that a rival on-premises edition of the Jira project management application from Atlassian will soon no longer be made available, noted Vignaud.

Finally, Rally Anywhere will also enable organizations to comply with any data sovereignty requirement that requires them to ensure data is stored within the physical borders of a specific country, he noted.

Rally is part of a portfolio of ValueOps value stream management (VSM) tools that Broadcom provides in both SaaS and on-premises editions. VSM traces its lineage back to lean manufacturing methods, which call for each step of a manufacturing process to be continuously measured. As software development has evolved from being a craft to a process that is automated as much as possible using DevOps best practices, an appreciation for the value of monitoring issues such as the impact of missed software development deadlines on the business has grown steadily, especially as more organizations realize how dependent on software they have become to drive revenue.

The overall goal is to make it possible to analyze normalized data collected from a diverse range of applications and services in a way that can also be more easily shared with applications such as Clarity, a workflow management application from Broadcom that is designed for business users, said Vignaud. That integration provides the business users regardless of what industry segment they operate in the visibility needed to manage an organization like a software company, he added.

It’s not clear how many software engineering teams might be looking to replace their existing approach to managing software engineering projects, but as it becomes simpler to automatically collect data from DevOps tools and platforms it’s becoming much easier to manage these projects. The days when project managers need to enter data they manually collected from software engineers have all but come to a close. Most of the data collection process has now been automated by modern project management applications.

The challenge now is applying artificial intelligence (AI) to that data to make it simpler to identify potential bottlenecks in software engineering workflows that might conspire to delay the development of an application. It may be still a while before those types of AI capabilities become pervasively employed but the one certain thing is that as project management continues to evolve many of the rote tasks that once made the job of the project manager tedious are rapidly being eliminated.

August 28, 2024
LambdaTest Kane Goes End-To-End on AI Testing

Cloud-based testing platform company LambdaTest has launched KaneAI, an end-to-end software AI test agent. With AI software in (some would say dire, or at least thorough) need of deep-level testing to eradicate hallucinations, to identify bias and to ensure that wider ratification systems are in place including retrieval augmented generation, there is much to test.

Overused by technology vendors spanning the networking, system observability and development lifecycle tools space, the term “end-to-end” in this context is the company’s pledge to offer tools that work at the authoring phase through to debugging and ongoing management, all through natural language so that teams create and execute automated tests.

What is End-To-End Testing?

A function much-beloved of software quality engineering teams (well, the effective ones at least), end-to-end testing quite specifically breaks down into five core stages in the LambdaTest world, if not others.

Phase #1 is planning, where tests are added to the test manager function.

Phase #2 is creation, KaneAI works to generate test scenarios in natural language.

Phase #3 is execution and scheduling so that tests can be run across various cloud instances i.e. a browser testing cloud, a visual regression testing cloud, a real device cloud (LambdaTest works to test websites and apps on 5000+ real Android and iOS devices) and a HyperExecute Cloud (the company’s test orchestration tool that automatically groups and distributes tests intelligently across different testing environments and takes into account past executions).

Phase #4 is debugging, where developers can debug tests using natural language commands.

Phase #5 is reporting, where team members can analyze test reports.

LambdaTest claims KaneAI to be the software testing industry’s first generative AI-powered test studio. Since the tests use natural language, it also provides an opportunity for different personnel (often less technical) to participate in the test-case creation process and then integrate tests into DevOps workflows.

Beefing Up Brittleness

“Automation testing has long been a critical part of software development, but it often comes with significant challenges. Test automation frequently lags behind development sprints, with brittle tests requiring constant maintenance. Even low-code/no-code solutions have a learning curve and often start to break down at scale, making it difficult for test automation setup to keep pace with evolving testing needs,” said Asad Khan, co-founder and CEO at LambdaTest.

Combined with built-in features including intelligent test planning, AI-powered test healing and advanced conditional assertions, KaneAI supports complex workflows and ensures comprehensive test coverage.

Where the LambdaTest team says that low-code/no-code solutions can hit scalability limits, KaneAI provides two-way test editing features, that enable users to either author in code or natural language. In addition, it allows multi-language code export across all major frameworks along with unique Instruction-to-Code and Code-to-Instruction translation features. This enables effortless maintenance of tests for scale and ensures that even the most intricate testing needs are met.

Workflow Wonderhorse?

CEO Khan suggests that his firm’s toolset is a happy revolution for the debugging process with its AI-powered test observability and real-time root cause analysis capabilities. This helps large-scale distributed engineering teams minimize application downtime and accelerate release cycles, without compromising on software product quality.

Whether KaneAI is as “revolutionary” as LambdaTest claims or not, it appears to be a precision-engineered product with an expansive set of functions, one might almost say end-to-end functionality. KaneAI integrates seamlessly with existing workflows, supporting popular tools such as Jira, Slack, GitHub Actions and Microsoft Teams.

August 27, 2024
Broadcom Virtual Cloud Foundation Update Streamlines DevOps Workflows

Broadcom at the VMware Explore 2024 conference today updated its VMware Cloud Foundation (VCF) platform to provide both deeper levels of integration, multitenancy capabilities and a single console through which all VCF components can be managed.

Paul Turner, vice president of products for the VCF division of Broadcom, said VCF 9 will substantially reduce the total cost of ownership (TCO) by, for example, eliminating the need for more than a dozen consoles that were previously required.

The overall goal is to make it simpler for IT teams to manage private clouds that can be deployed either in an on-premises IT environment or on a public cloud service, said Turner.

As part of that effort, Broadcom is also making virtual private cloud (VPC) maturity assessment, training and jumpstart services.

Additionally, Broadcom is adding an Advanced Memory Tiering with NVMe capability to VCF 9 that makes it more cost-effective to run data-intensive applications. VCF 9 also makes it possible to manage fleets of virtual machines, including security operations augmented by generative artificial intelligence (AI), and deploy virtual machines as much as 61% faster.

At the same time, network virtualization elements of the platform based on VMware NSX are better integrated with VMware ESXi to streamline operations, noted Turner. Virtual private clouds (VPCs) can also now take advantage of services such as VMware vDefend to enable security groups and VMware Avi Load Balancer to enable one-click deployment of load-balancing capabilities. The VMware hypervisor can now also serve as a threat for vDefend.

A VCF Import tool will make it easier to import VMware NSX, VMware vDefend, VMware Avi Load Balancer and more complex storage topologies into existing VCF environments. VCF 9 also now supports native vSAN-to-vSAN Data Protection with Deep Snapshots to improve resiliency.

Finally, Broadcom is making it easier to deploy VMware Private AI Foundation with NVIDIA capabilities on top of VCF 9 by adding support for virtual graphics processor unit (vGPU) profile visibility, GPU reservations, a data indexing and retrieval service, and an AI agent builder service.

It’s not clear how many enterprise IT organizations are signing up for VCF. Broadcom is providing additional capabilities to make VCF attractive, but many IT organizations have already invested in other networking, storage and security platforms. In addition, many DevOps teams have adopted alternative platforms for accelerating the building and deployment of applications that don’t necessarily depend on what virtual machine is employed.

Many IT organizations are also still trying to determine what their total costs under a subscription license are compared to the perpetual licensing model for VMware which is no longer an option. The primary issue is not so much migrating workloads but rather the degree to which it makes economic sense to deploy additional workloads on VMware platforms.

At a time when IT organizations are increasingly sensitive to the total cost of IT, however, there is a case to be made for consolidation. The challenge is convincing IT teams they will not become beholden to a single vendor that might in the future increase licensing fees after they no longer have any other viable alternatives.

August 27, 2024
Action and Intention

August 27, 2024