Nine Community awards recognize the people, teams, projects and content that power DevOps. Fifteen Tools & Services awards spotlight the platforms and solutions shaping the next era of software delivery.
An established OSS project demonstrating adoption, sustained contribution and measurable impact.
A younger project or major new initiative that introduced a genuinely different approach during the award year.
The often-unrecognized work of maintaining, governing and sustaining an important project.
Community building, mentoring, advocacy and contributions beyond promoting a commercial product.
A practitioner at an end-user organization who led meaningful organizational or technical change.
An enterprise team and its demonstrated software-delivery outcome. No vendor-led nomination presented as a product case study.
An enterprise-developed application of AI or agents that improved delivery, quality, reliability or developer experience.
Any book, article, podcast, video, course or independent research.
Meetups, mentoring programs, community conferences, hackathons, training initiatives and other community-led programs.
Requires a named or verifiable customer outcome, not merely a product description.
Broad, integrated platforms covering multiple parts of planning, building, securing, releasing and operating software.
Human-directed coding, review, documentation, test generation, planning and developer assistance.
Agents that plan and execute multi-step work across repositories, pipelines, deployments or operations.
MLOps, LLMOps and AgentOps: deployment, evaluation, observability, governance and lifecycle management of AI systems.
Self-service, golden paths, platform orchestration, governance and developer enablement.
Developer productivity, workflow friction, engineering analytics and outcome measurement.
Build, integration, deployment, progressive delivery, release management and rollback.
Functional, performance, reliability and AI-assisted testing across the lifecycle.
Application security, secure development, policy, secrets and security integrated into development workflows.
Dependencies, artifacts, SBOMs, provenance, attestations, signing and pipeline integrity.
Telemetry, incident response, service reliability, remediation and operational intelligence.
Infrastructure as code, configuration, provisioning, environment automation and cloud operations.
Cost, capacity, cloud and AI consumption, unit economics and engineering-value optimization.
A genuinely new commercial product or major new platform introduced during the eligibility year.
Full award descriptions, updated for the 2026 program.
For an established, mature open source project in the DevOps space with a demonstrated track record — not a new or experimental effort. Judges will look for breadth of real-world adoption, the health and size of the contributor community, sustained release cadence and maintenance, and evidence of measurable impact on how teams build, test, secure, deploy, or operate software.
Limited to open source projects that were launched or substantially advanced during the last 36 months. The project will be judged on the originality of its approach rather than its scale of adoption. Nominations should explain what is genuinely different about the project's approach compared to existing tools, and why it represents a meaningful step forward for the community even if it is still building its user base. Keeping this separate from Most Impactful Open Source DevOps Project ensures new ideas aren't competing against established projects on adoption numbers alone.
Recognizes an individual whose ongoing work maintaining, governing, and sustaining an important open source project keeps that project healthy and usable — work that is essential but often invisible to end users. Nominations should highlight specific contributions such as triaging issues, reviewing and merging pull requests, stewarding project governance and roadmap, and supporting the contributor community, rather than just code commits. This award celebrates the discipline of maintainership itself, separate from the project's own impact or innovation, which are covered by the two categories above.
For an individual who has built community, mentored practitioners, or advocated for DevOps practice in ways that go beyond promoting a commercial product or employer. Nominations should point to specific community-building activities during the eligibility year — organizing meetups, mentoring newcomers, running forums or discussion groups, or otherwise strengthening the broader DevOps community. Vendor employees are eligible only where the nominated activity is genuinely community-serving rather than a vehicle for product marketing.
Honors a practitioner or leader at an end-user organization — not a vendor — who drove meaningful organizational or technical change in how their company builds, delivers, or operates software during the eligibility year. Nominations should describe the specific change this person led (a transformation initiative, a platform shift, a cultural or process change) and the outcomes that resulted, with enough detail to verify the impact. This category is reserved for practitioners inside the organizations that use DevOps tools and practices, not for vendor executives or evangelists.
Recognizes an enterprise team and a specific, demonstrated software-delivery outcome they achieved — the team-level counterpart to the individual leadership award above. Nominations must be submitted as a genuine end-user story told from the team's perspective, with named outcomes and metrics; vendor-authored submissions that are effectively a product case study dressed up as a customer nomination are not eligible. Vendors with a strong customer story should instead nominate in the Tools & Services track's Best Customer DevOps Implementation category.
For an enterprise's own use of AI or AI agents — built, configured, or applied internally — that measurably improved software delivery, quality, reliability, or developer experience. This is the community-track counterpart to the AI categories in Tools & Services: it celebrates what an end-user organization did with AI, not the commercial tool or platform itself. Nominations should name the organization and describe the specific use case and its measured impact, distinguishing genuine internal application from a vendor pitching its own AI product.
For any book, article, podcast, video series, course, or piece of independent research that has educated or influenced the DevOps community during the eligibility year, regardless of publication format or platform. Judges will weigh the quality of the ideas, the clarity of the explanation, and its reach or influence among practitioners. This category consolidates content formats under one roof, so nominators should highlight what makes the specific piece exceptional rather than simply naming a prolific author or channel.
For meetups, mentoring programs, community-run conferences, hackathons, training initiatives, or other structured community-led programs — not a single piece of content or an individual leader — that brought DevOps practitioners together and delivered lasting value during the eligibility year. Judges will look for reach, consistency, participant impact, and evidence that the program strengthened the community beyond a single one-off gathering.
Recognizes a real-world DevOps transformation delivered for or by a named, verifiable end-user organization — not a vendor's product capabilities in the abstract. Submissions must identify the customer (or provide verifiable proof of the engagement if anonymized) and describe the starting problem, the solution implemented, and measurable business or technical outcomes such as deployment frequency, lead time, incident reduction, or cost savings. Entries that only describe a product or platform without a demonstrable, attributable customer story are not eligible for this category.
For broad, integrated platforms that span multiple stages of the software delivery lifecycle — planning, building, securing, releasing, and operating — rather than a single point solution. Judges are looking for breadth of coverage, depth of native integration across those stages, and evidence that the platform reduces tool sprawl or hand-offs for engineering teams. Point solutions that excel at one lifecycle stage should instead be nominated in the category that matches their primary focus (e.g., CI/CD, testing, security).
For tools that use AI to help a human developer plan, write, review, document, or test code faster and better — with the human remaining firmly in the driver's seat. This includes AI pair-programming and code completion, AI-assisted code review, automated documentation generation, AI-generated test cases, and AI-based sprint or task planning assistance. The defining trait is human-directed use: the developer initiates, guides, and approves the work, and the AI accelerates rather than replaces their judgment.
For autonomous or semi-autonomous AI agents that plan and execute multi-step work across the software delivery chain — spanning repositories, CI/CD pipelines, deployments, or production operations — with reduced ongoing human direction at each step. This differs from the AI-Assisted category in the level of autonomy: entries here should demonstrate agents that decompose a goal into tasks, take actions across multiple systems, and adapt based on results, not just single-turn assistance. Examples include agents that triage and resolve pull requests end to end, orchestrate multi-service deployments, or autonomously remediate pipeline failures.
Covers MLOps, LLMOps, and AgentOps: the deployment, evaluation, monitoring, governance, and full lifecycle management of AI models, LLM-based applications, and autonomous agents themselves — treating AI systems as the thing being operated, not the tool doing the operating. This includes model/version registries, prompt and evaluation pipelines, AI observability and drift detection, guardrails and policy enforcement, and cost or performance management for AI workloads in production. This category is the mirror image of the two above: it is about operationalizing AI, not about AI helping to operationalize software.
For solutions that give engineering organizations self-service infrastructure and workflows through golden paths, internal developer portals, and platform orchestration. Judges will look for evidence of developer self-service, standardized paved roads that reduce cognitive load, built-in governance and guardrails, and measurable developer enablement outcomes such as faster onboarding or reduced ticket volume to platform teams.
For tools focused on measuring and improving developer productivity, identifying workflow friction, and surfacing engineering analytics that connect activity to outcomes. This includes DevEx survey and sentiment tools, engineering intelligence dashboards, flow-metrics and DORA-metric reporting, and solutions that help leaders correlate investment in developer experience with delivery results. Entries should emphasize measurement and insight rather than platform infrastructure itself.
For solutions focused on the mechanics of getting code from commit to production: build automation, continuous integration, GitOps-based deployment models, progressive delivery techniques (canary, blue-green, feature flags), release orchestration and management, and rollback capability. Judges are looking for breadth of solution including features that deliver reliability, speed, and control across the build-to-release pipeline, including how well a solution handles failure and recovery.
For solutions that validate software quality across the delivery lifecycle, including continuous testing, functional, performance, reliability, and increasingly AI-assisted testing (such as AI-generated test cases, self-healing test scripts, or intelligent test selection and prioritization). Judges will look for breadth of testing coverage, integration into CI/CD workflows, and how effectively the solution reduces manual QA burden while catching real defects earlier.
For solutions that embed application security directly into the development workflow rather than bolting it on afterward — including secure coding practices, policy-as-code enforcement, secrets detection and management, and vulnerability identification integrated into the developer's existing tools and pipelines. Judges will look for how seamlessly security is woven into everyday development activity and how effectively the solution reduces friction between developers and security teams.
For solutions focused specifically on the integrity and provenance of the software supply chain: dependency and open-source risk management, artifact and container security, Software Bill of Materials (SBOM) generation and management, build provenance and attestations, code and artifact signing, and protection of the CI/CD pipeline itself from tampering. This category is distinct from general DevSecOps in its specific focus on what goes into a build and proof of where it came from, rather than the broader application security workflow.
For solutions that give teams visibility into and control over how software behaves in production, including telemetry collection (logs, metrics, traces), incident detection and response, service reliability and SRE practices, automated remediation, and operational intelligence. Judges will look for the breadth and depth of telemetry, speed of detection and resolution, and evidence of measurable reliability improvements such as reduced MTTR or improved SLO attainment.
For solutions that automate the provisioning, configuration, and ongoing operation of infrastructure and cloud environments, including infrastructure as code, configuration management, environment automation, and multi-cloud or hybrid-cloud operations tooling. Judges will look for how effectively the solution eliminates manual infrastructure work, enforces consistency across environments, and scales operational management as infrastructure grows.
For solutions that help organizations understand and optimize the cost of engineering and AI operations, including cloud cost visibility and management, capacity planning, AI/compute consumption tracking, unit economics analysis, and tools that translate engineering spend into business value. Judges will look for how directly a solution ties cost data to actionable optimization and how it helps teams balance efficiency with delivery velocity — including the fast-growing challenge of managing AI inference and compute costs.
For a new commercial product or a major new platform introduced during the previous 24 months — not an incremental update to an existing offering. Judges are looking for novelty and impact: solutions that introduce a meaningfully new approach, capability, or category to the DevOps and software development market, with particular attention this year to breakthroughs driven by AI. This category exists to spotlight innovation itself, separate from how well an established product performs within its category.
Community nominations are free. Tools & Services entries are $300 per nomination.