Operations | Monitoring | ITSM | DevOps | Cloud

AI SRE Agent with Temporal, ClickHouse, and Codex: AURA in a Gated Run

1,133 requests failed on one bad commit. The patch and the regression test are already written by the time anyone is asked to read the exact diff. This demo runs AURA as one step inside a Temporal workflow, alongside Codex. A GET request against a product catalog service goes from success to HTTP 500, and ClickHouse records the version, commit, trace ID, and exact error for every request. By the time AURA investigates, all 1,133 requests on that version have failed.

You can't audit an AI model the way you audit a binary

Open up an AI model and what's actually inside is a floating array of decimal points. No one can look at that and confirm it hasn't been tampered with, doesn't contain bias, or wasn't trained on poisoned data. This video covers why that changes how you need to think about trusting a model: If you can't unpick the model itself, you have to be able to trust its origin.

A Practical ClickHouse Monitoring Guide Built Around Failure Modes

Why does a ClickHouse cluster report every node as healthy while inserts start failing and dashboards go stale? Most often the failing subsystem was never represented in the metrics anyone had on screen. A node answers its health check while its replication queue has been growing for hours. ClickHouse breaks in specific, repeatable ways. Parts accumulate faster than background merges can consolidate them. Coordination drops quorum and every replicated table quietly turns read-only.

What Backup Monitoring Software Should Track to Protect RTO and RPO

How many backup jobs completed successfully in your environment last night, and how many of those systems could you bring back inside the window the business agreed to? Most backup consoles answer the first question well. They report job status, completion time and volume written, then roll it into a reassuring compliance summary. The second question needs different evidence, usually missing from that screen. The distance between those answers shows up during the recovery attempt.

The AI trust dial: from local agents to autonomous software factory

There are many conversations about the use of AI, particularly how engineering teams are using it in their coding workflows. Manual work is being replaced by agent-driven automation, and human value increasingly lies in the higher-order work: writing specs, thinking through architecture, steering the direction, exercising taste, and reviewing the output.

Shipped: Cost alerts in the Google Chat space where your team already works

If your company runs on Google Workspace, your team lives in Google Chat. That is where the standup happens and where threads turn into decisions. Cost alerts can now go there too. This is relevant because an alert only does something if it reaches people in a place where they can talk about it. Email is great for a record but not great for a reaction. An anomaly notification sitting in an inbox waits for that person to open it, decide it is real, and then go tell everybody else.

Zero-Code Instrumentation in Kubernetes Without the Instrumentation CRD

The OpenTelemetry Operator changed how teams approach telemetry collection in Kubernetes. The core appeal of zero-code instrumentation is that you can bring up telemetry inside application containers to collect traces, metrics, and logs without touching your source code or rebuilding your container images. However, if you follow the default OpenTelemetry Operator documentation, you quickly run into a heavy operational prerequisite: the Instrumentation CRD.

How AI Answer Engines Like Perplexity Choose Which Brands to Cite in 2026

More product research now starts inside an AI assistant instead of a search engine. When someone asks ChatGPT, Perplexity or Google's AI Overviews for the best option in a category, they get a short written answer that names a few brands and links to a handful of sources. The brands that are named win the attention. The rest are not shown at all.

How ArcSonic Tech Limited Approaches System Architecture Reviews for Scalability Readiness

Most systems fail to scale, not because the team didn't work hard enough, but because the architecture was designed for the load it had rather than the load it would eventually face. The features worked. The performance was acceptable. The code was clean enough. But the structural decisions made early - about how data flows, how services communicate, where state lives - created ceilings that only became visible when the traffic arrived.

Best Voice AI Orchestration Platforms in 2026

Building an AI voice agent can be easy, but making it actually work on real phone calls is more challenging. Voice AI orchestration platforms help to connect speech-to-text, text-to-speech, and telephony networks into real-time conversational agents. Although these tools are AI-powered, they handle turn-taking and interruptions during web interactions. By using these platforms, you will get fluid voice conversations that are ready to use.