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Opsera, a startup that’s building an orchestration platform for DevOps teams, today announced that it has raised a $15 million Series A funding round led by Felicis Ventures. Founded in January 2020, Opsera lets developers provision their CI/CD tools through a single framework. There were many engineering teams.
The growing market for sales tools has given rise to a curious cottage industry: DevOps startups specifically targeting the software used in sales and marketing functions. Here, “DevOps,” refers to tools that automate processes between software development and IT teams.)
It is common for people to confuse these two prominent career options – DevOps Engineer and Software Engineer. Role of DevOps Engineer. The DevOps Engineer is responsible for everything from coding to updating, developing, to maintaining the software. Scripting, tools, communication, collaboration, etc., Dependence.
Each year, the DevOps Dozen Awards recognize the best and brightest in the DevOps community and industry, celebrating individuals and organizations making a significant impact. We are thrilled to announce the winners of […]
Speaker: Leo Zhadanovsky, Principal Solutions Architect, Amazon Web Services
To get there, Amazon focused on decomposing for agility, making critical cultural and operational changes, and creating tools for software delivery. Whether you're developing for a small startup or a large corporation, learning the tools for CI/CD will make your good DevOps team great. The "two pizza" team culture.
It may surprise you, but DevOps has been around for nearly two decades. Driven by the development community’s desire for more capabilities and controls when deploying applications, DevOps gained momentum in 2011 in the enterprise with a positive outlook from Gartner and in 2015 when the Scaled Agile Framework (SAFe) incorporated DevOps.
These agents are becoming critical in transforming DevOps and cloud delivery processes. These agents are not just simple tools they are flexible systems that can make informed decisions by using the data they collect and their knowledge base. A key development in this area is intelligent agents.
When should you even start thinking about MLOps, or when is plain DevOps wiser to focus on first? Operations ML teams are focused on stability and reliability Ops ML teams have roles like Platform Engineers, SRE’s, DevOps Engineers, Software Engineers, IT Managers. Enter DevOps. What are the prerequisites for MLOps?
. — Anna Dev tools plus generative AI Y Combinator Demo Days are a strong indicator of the trends investors might be interested in — and that’s one of the main reasons why TechCrunch always watches them pretty closely. In its Winter 2023 batch , three areas stood out, the accelerator said: “ open source , dev tools and AI.”
Speaker: Dave Mariani, Co-founder & Chief Technology Officer, AtScale; Bob Kelly, Director of Education and Enablement, AtScale
It includes on-demand video modules and a free assessment tool for prescriptive guidance on how to further improve your capabilities. Translating DevOps principles into your data engineering process. Check out this new instructor-led training workshop series to help advance your organization's data & analytics maturity.
MLOps platform Iterative , which announced a $20 million Series A round almost exactly a year ago, today launched MLEM, an open-source git-based machine learning model management and deployment tool. The separate tools bring a modular, Unix philosophy to ML model management and ModelOps.,” ” Image Credits: Iterative.
Dagger, which was co-founded by Hykes and his fellow Docker alums Sam Alba and Andrea Luzzardi , aims to build what the team calls a “devops operating system.” The co-founders went looking for problems they could solve for the developer community and it quickly became clear to them that the DevOps process remains a bottleneck.
Lifecycle Development With AI We have seen a huge shift in the way developers and consultants are using Generative AI (GenAI) tools to create working microservices.
The DevOps ecosystem of today is becoming increasingly more complex. As development teams grapple with the challenge of modernizing their DevOps toolchains, a number of concerns and challenges have followed closely behind. Chief among those challenges? What’s the state of DevSecOps today?
Today, IT encompasses site reliability engineering (SRE), platform engineering, DevOps, and automation teams, and the need to manage services across multi-cloud and hybrid-cloud environments in addition to legacy systems. At the same time, the scale of observability data generated from multiple tools exceeds human capacity to manage.
During his one hour forty minute-keynote, Thomas Kurian, CEO of Google Cloud showcased updates around most of the companys offerings, including new large language models (LLMs) , a new AI accelerator chip, new open source frameworks around agents, and updates to its data analytics, databases, and productivity tools and services among others.
Despite the talk about how automation can make employees and businesses more productive, managing it across the entire DevOps chain is a complex task. Especially as companies increasingly adopt hybrid cloud infrastructure, addressing the growing complexity in the DevOps toolchain requires total visibility and control of end-to-end processes.
The open source dynamic runtime code analysis tool, which the startup claims is the first of its kind, is the brainchild of Elizabeth Lawler, who knows a thing or two about security. ” Code analysis tool AppMap wants to become Google Maps for developers by Carly Page originally published on TechCrunch.
It’s no secret that companies are committing to DevOps. In fact, according to a recent survey, three-quarters of leaders have adopted DevOps into their operations. DevOps delivers speed and agility to the development process. Change management brings consistency to DevOps. But it’s not easy.
. “Moreover, we saw how difficult it was for the revenue operations team to do their job — how they constantly struggled between different areas of responsibility — and we decided that we want to create a tool that would change their day-to-day.” billion by 2025 ( according to Statista) and that Salesforce had a 32.2%
Infrastructure as Code (IaC) and DevOps have come together to completely reshape the cloud landscape over the last few years. For the uninitiated, IaC is a fundamental DevOps practice – a core component of continuous delivery. In fact, they already have a competing open source IaC tool in Ansible.
Enter robotic process automation (RPA) : a smart set of tools that deploys AI and low-code options to simplify workflows and save everyone time while also adding safeguards that can prevent costly mistakes. Many RPA platforms offer computer vision and machine learning tools that can guide the older code. What is RPA?
DevOps fueled this shift to the cloud, as it gave decision-makers a sense of control over business-critical applications hosted outside their own data centers. Data engineers play with tools like ETL/ELT, data warehouses and data lakes, and are well versed in handling static and streaming data sets. The proliferation of ML tools.
TL;DR: Chancing the narrative on GitHub Copilot from focus on engineers to focus on a sturdy (DevOps) foundation to be able to go faster. Next frontier: the rest of our organization Premise: current narrative is not helping In my opinion we need to shift the narrative on enabling engineers to use GitHub Copilot.
People : To implement a successful Operational AI strategy, an organization needs a dedicated ML platform team to manage the tools and processes required to operationalize AI models. This team serves as the primary point of contact when issues arise with models—the go-to experts when something isn’t working.
Salesforce DevOps is revolutionizing the application lifecycle management (ALM) process by unifying development and operations. Through tools like DevOps Center, CI/CD integrations, and source control systems, teams can collaborate more effectively, automate repetitive tasks, and deliver higher-quality releases faster.
Introduction In today’s data-driven world, business intelligence tools are indispensable for organizations aiming to make informed decisions. Version control systems (VCS) are essential tools in modern software development, offering a structured way to manage changes, track history, and facilitate collaborative efforts among teams.
Speed: Does it deliver rapid, secure, pre-built tools and resources so developers can focus on quality outcomes for the business rather than risk and integration? Alignment: Is the solution customisable for -specific architectures, and therefore able to unlock additional, unique efficiency, accuracy, and scalability improvements?
” Xebia’s Partnership with GitHub As a trusted partner of GitHub, Xebia was given early access to the new EU data residency environment, where it could test its own migration tools and those of GitHub to evaluate their performance. The post GitHub Removes Data Barriers for EU Enterprises appeared first on Xebia.
Why FinOps is failing FinOps a framework formed by combining Finance and DevOps was introduced in the early 2010s as cloud adoption surged, addressing financial accountability and cost optimization in the cloud. Overemphasis on tools, budgets and controls. A fundamental change in approach is urgently needed. Neglecting motivation.
More than half of professional developers have CI/CD, DevOps and automated testing tools and services available at their organization, Stack Overflow’s 2022 developer survey uncovered. However, Stack Overflow noted, only 38% of the 34,906 respondents reported having a developer portal to make it easy to find tools and services.
By automating the deployment of Sitecore hotfixes with an Azure DevOps pipeline, you can ensure faster, more reliable updates while reducing human error and minimizing downtime. In this post, well walk you through how to automate this process using Azure DevOps. Having a quick, automated process to apply these updates is crucial.
Introduction As organizations scale their DevOps practices, the need for efficient resource management and automation becomes critical. These pipelines require a complex set of tools installed on self-hosted Azure DevOps agents. KEDA in the Context of Azure DevOps Agent Pools For scenarios like my own.
Microsofts Azure infrastructure and ecosystem of software tooling, including NVIDIA AI Enterprise, is tightly coupled with NVIDIA GPUs and networking to establish an AI-ready platform unmatched in performance, security, and resiliency.
The rise of new technologies Looking at the current rise of new technologies, tools, and ways of working, you would think we are trying to prevent a new software crisis. Take, for example, DevOps, which seeks to streamline development and operations. But DevOps is just one of many examples.
This blog offers a comprehensive guide to setting up Continuous Integration (CI) in Azure DevOps to automate the integration of SharePoint Framework (SPFx) code by leveraging Azure DevOps pipelines. Login to Visual Studio Online (Azure DevOps) Select your project to set up a build definition. tool installer.
For example, IBM has developed hundreds of tools and approaches (or “journeys”) over the last 25 years which facilitate the modernisation process in organisations and meet a broad range of requirements. These have all been grouped together now on a platform known as the IBM Consulting Cloud Accelerator.
With features like pull requests, issue tracking, and code reviews, GitHub has become a vital tool for open-source and professional software development. It supports Git, a distributed version control system that allows multiple contributors to work on projects simultaneously. Introduction Howdy!
Additionally, Dynatrace unveiled an Observability for Developers module for its platform that includes a Live Debugger tool that will be made generally available in 90 […]
How AI-powered DevOps is setting new standards for efficiency By Matthew Smith Posted in Operations Published on: March 26, 2025 Last update: March 26, 2025 Software development should be fast, but for many teams, it still feels like wading through quicksand. DevOps was meant to speed things up, but inefficiencies remain.
As organizations migrate to the cloud, it’s clear the gap between traditional SOC capabilities and cloud security requirements widens, leaving critical assets vulnerable to cyber threats and presenting a new set of security challenges that traditional Security Operations Center (SOC) tools are ill-equipped to handle.
Seemplicity is a portmanteau of “see” and “simplicity”, and that is effectively what it is doing: helping DevOps and SecOps teams see a more complete picture of the state of an organization’s security, by simplifying how to view it.
“[We enable] people in business to create apps to help them in their working life — so things like customer portals, internal tools and things that take the data they’re already using, often to run a process, and turn that into an app,” Skelly explained.
Manish Limaye Pillar #1: Data platform The data platform pillar comprises tools, frameworks and processing and hosting technologies that enable an organization to process large volumes of data, both in batch and streaming modes. Pillar #2: Data engineering This function is responsible for transforming raw data into curated data products.
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