Operations | Monitoring | ITSM | DevOps | Cloud

Harness Dynamic Pipelines offers an option to create pipelines, or pipeline stages, at runtime For a long time, CI/CD has been “configuration as code.” You define a pipeline, commit the YAML, sync it to your CI/CD platform, and run it. That pattern works really well for workflows that are mostly stable. But what happens when the workflow can’t be stable? In all of those cases, forcing teams to pre-save a pipeline definition, either in the UI or in a repo, turns into a bottleneck.

Over the past year, Harness’s India organization has entered a new phase of growth – one defined not just by scale, but by increasing technical depth and impact. What began as steady expansion has turned into real momentum across engineering, product, and operations. Today, 480 people work in India, contributing across every major product area. In 2025 alone, the team in India grew by more than 75%, and now each core Harness product offering has a strong engineering presence in the region.

AI will not fix broken software delivery. It will expose it. By 2026, teams that win will use specialist AI agents, guardrails over gates, and security built directly into the pipeline. As we look toward 2026, it is becoming clear that AI is not just changing how code is written. It is changing how software delivery itself works. The real shift is happening at the intersection of AI, security, and developer experience, where speed, risk, and responsibility now collide.

Chaos fault validation must be safe, predictable, and measurable. High setup friction blocks adoption and slows feedback loops. API-driven execution beats manual YAML workflows. Real-time logs and smart target discovery speed debugging. Dual-phase validation ensures impact and recovery. Strong DX enables faster, scalable chaos testing. As an enterprise chaos engineering platform vendor, validating chaos faults is not optional — it’s foundational.

Knowledge graphs and RAG (Retrieval-Augmented Generation) are complementary techniques for enhancing large language models with external knowledge, and each brings unique strengths for DevOps use cases. While they are often mentioned together, they are fundamentally different systems, and combining them delivers far better outcomes than relying on either approach alone.

Cloud migration is a multi-layer transformation involving infrastructure, CI/CD, governance, security, and cost management—not just application movement. Enterprises face unique migration challenges due to complex systems, parallel cloud operations, compliance requirements, and tool sprawl. Automation and standardization are critical to reducing risk, manual effort, and operational inconsistency during cloud-to-cloud migrations.

Harness Database DevOps now natively supports Google AlloyDB, enabling enterprises to manage PostgreSQL-compatible schema changes with CI/CD, GitOps, and policy-driven governance. Teams gain faster, safer, and fully auditable database delivery while reducing operational risk and manual overhead across environments. As organizations double down on cloud modernization, Google Cloud’s AlloyDB for PostgreSQL is quickly becoming the preferred engine for mission-critical applications.

Since launching Harness in 2017, we’ve been on a mission to unlock faster innovation by removing the bottlenecks that slow software engineering teams down. From day one, we believed that the biggest obstacles in engineering weren’t in writing code — they were in everything that followed.

Forget the ticket queues and slow handoffs. Harness Workflows let developers spin up services, environments, and everyday ops tasks in minutes. It’s self-service that’s fast, safe, and actually fun to use. A developer once told me, half-joking and half-frustrated, “I spend more time waiting than coding.” It wasn’t the dramatic kind of waiting, like an hour-long debugging session or a blocked deployment at midnight.

Developer velocity and DBA caution are not opposing forces, they reflect two essential priorities that historically lacked a shared process. Database DevOps eliminates tension by introducing automated validation, approvals, and visibility that allow developers to move fast while DBAs safeguard performance and reliability. With platforms like Harness, database change becomes a collaborative workflow instead of a conflict, turning release cycles into a partnership built on trust and predictability.