Autoptic Expands Systems Change Resilience Catalog to 250 Reusable Components for Preventative AI SRE

Catalog now includes 21 Data Sources, 110 Tools, 94 Skills, and 25 Agents, giving engineering teams an expanded foundation for change-resilient software systems

AUSTIN, TX, UNITED STATES, August 19, 2026 /EINPresswire.com/ -- Autoptic Inc., an innovator in AI DevOps focused on Systems Change Resilience, today announced a significant expansion of its extensible foundation for rapid pathways to customer value: the Catalog. The Autoptic Catalog now includes 21 Data Sources, 110 Tools, 94 Skills, and 25 Agents.

Together, these 250 reusable, customizable, and extensible components provide software engineering, platform engineering, DevOps, and SRE teams with a robust foundation for detecting production risk, investigating complex systems degradations, automating operational workflows, and building organization-specific approaches to Systems Change Resilience.

Autoptic originally unveiled the Change Resilience Catalog in May 2026 as a curated library of reusable building blocks. At the time, the Catalog included 95 components: 15 Data Sources, 40 Tools, 30 Skills, and 10 Agents. Since then, customer deployments and implementations have substantially expanded every layer of the Catalog.

“The Autoptic Catalog is designed to compound,” said Steve Semelsberger, Co-Founder & CEO of Autoptic. “When we solve an important problem with one customer, we have the opportunity to turn that work into a reusable component that other customers can adopt, contextualize, and extend. Customers get faster time-to-value, while the Autoptic platform becomes more impactful with every implementation.”

A Growing Foundation for Change Resilience

The expanded Autoptic Change Resilience Catalog now includes:
+ 21 Data Sources that connect Autoptic to telemetry, events, issues, changes, repositories, and other information distributed across modern engineering environments, read in place, without relocating data. Integrations include cloud platforms like AWS (CloudWatch, CloudTrail, Cost Explorer), observability stacks such as Datadog and Grafana's ecosystem (Prometheus, Loki, Tempo), and delivery and tracking systems like GitHub, GitLab, and Jira, among others.

+ 110 Tools that provide packaged, deterministic computational and analytical capabilities across those Data Sources. Each Tool is a versioned Performance Query Language (PQL) program (a bounded, repeatable analysis rather than a free-form prompt) that returns charts, notes, and ranked entities. Tools reach across the stack, including cloud infrastructure (EC2, Lambda, S3), Kubernetes internals (etcd, HPA, PVC), data layer (PostgreSQL, Kafka, Redis) and application insights (JVM, Node.js event loop). Tools are authored as ordinary code: reviewable, diffable, and manageable through AI coding systems like Claude.

+ 94 Skills that combine Tools into predictable operational tasks and workflows aligned with work routinely performed by DevOps and SRE teams. Examples include triage playbooks for services and databases; Kubernetes operations like autoscaler and PVC-fill diagnostics; and delivery workflows such as GitHub Actions pipeline health checks. Skills support both structured workflows (fixed Tool sequences with schedules and notification floors) and more exploratory Detective pathways that classify operator intent and orchestrate the optimal Skill.

+ 25 Agents that combine Skills, Tools, prompts, AI inference, and orchestration to deliver higher-level operational capabilities optimized for a customer's production stack. Agent families cover areas like platform and orchestration reliability, database systems, infrastructure and networking, and release management. Agents power timed and triggered Briefs along with on-demand Investigations.

“Raw component counts are interesting, but what matters is how these pieces work together,” said Peco Karayanev, Co-Founder & CTO of Autoptic. “Sources provide the operational context. Tools perform precise computations. Skills establish repeatable pathways for getting work done. Agents coordinate those capabilities to investigate, reason, notify, and act. The Catalog allows us to continually expand what Autoptic can accomplish while maintaining the control, transparency, and extensibility that production engineering teams require.”

From Customer Challenges to Reusable Capabilities

The rapid expansion of the Catalog reflects Autoptic’s approach to developing its platform in close collaboration with customers. Rather than treating each implementation as a standalone project, Autoptic looks for repeatable patterns within customer systems. New integrations, analyses, workflows, change types, and agentic capabilities become reusable Catalog components, creating a growing base of capabilities available to both existing and future customers.

This creates a flywheel: customers help shape new capabilities; those capabilities become reusable building blocks; and the expanding library enables subsequent customers to solve similar problems more quickly.

Producing Significant Customer Impact

The Autoptic platform and Catalog components have provided critical customer value. For example, at a digital banking platform company serving hundreds of U.S. financial institutions, a scheduled Autoptic database-reliability Agent surfaced a failover 25 minutes before it was recognized by the default observability system. In a separate event affecting a member-facing banking service, Autoptic was the only system that detected the degradation.

At a live-events technology company operating under weekly peak-traffic surges, Autoptic identified a progressive memory-growth pattern in a production service and flagged it as it developed—before it reached a threshold that would have triggered a customer-facing failure during a peak traffic weekend.

For a global AI agent platform provider, Autoptic analysis of observability data volume and cardinality identified approximately $60K per month of recoverable overage spending.

An Open Approach to AI SRE and AI DevOps

The Change Resilience Catalog operates within Autoptic’s broader Systems Change Resilience platform, which helps engineering organizations better detect and address latent production degradations, preventing customer-impacting incidents as part of a broader AI SRE strategy.

The platform supports both Autoptic-hosted and Bring Your Own Cloud (BYOC) deployments and is designed around an open approach to AI, enabling organizations to use commercial and open-source models while maintaining control over data, infrastructure, permissions, workflows, and inference costs.

“Our goal is not to replace the DevOps and SRE ecosystems our customers have spent years building,” Semelsberger added. “It is to make those ecosystems more intelligent, interconnected, change-aware, and resilient.”

About Autoptic
Autoptic is collaboratively designing and building the emerging practice of Systems Change Resilience, helping CTOs and software engineering organizations move faster, absorb more change, calibrate risk, and build stronger software systems in an increasingly complex, AI-fueled world. Autoptic integrates with observability, incident management, infrastructure, software delivery, and other DevOps systems to help engineering teams detect production degradations earlier, investigate complex environments faster, and better manage operational costs. The company was co-founded by software industry veterans and is backed by 35 professional investors, including 9 CTOs. Autoptic was named one of 12 “Austin Startups to Watch in 2026” by the Business Journal.

Steve Semelsberger
Autoptic Inc
email us here
Visit us on social media:
LinkedIn