Operations | Monitoring | ITSM | DevOps | Cloud

Load Testing Kafka #speedscale #kafka #loadtesting

Message brokers are a critical component of modern distributed systems, facilitating asynchronous communication between services. Load testing message broker integrations requires special considerations since the interaction patterns differ from traditional HTTP-based APIs. Speedscale provides specialized tooling to help you load test applications that integrate with message brokers by.

CTO Predictions for 2026: Special ShipTalk Episode with Nick Durkin

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.

How AI-Native Data Pipelines Help Create a Security Data Lake

Security teams are generating and storing more telemetry than ever before. Logs, metrics, traces, and events come from cloud services, applications, identities, and infrastructure across many environments. Retention requirements continue to grow, yet the cost of storing all of this data in traditional hot storage can quickly exceed annual budgets. At the same time, investigations and audits rely on fast access to historical data, and any delay can slow response time or limit visibility.

Get Kafka-Nated Special Episode: A Kristmas Kafka

Join us for A Kristmas Kafka, an informal and deeply technical roundtable with Apache Kafka committers, contributors and community leaders. This conversation brings together the people closest to the Kafka codebase to reflect on where the project started, how it has evolved and what lies ahead for streaming systems.

Part 3: What If IT Stopped Reacting to Incidents and Started Predicting Them?

Enterprises are experiencing a turning point. Systems scale faster than teams can, AI is rewriting the rhythms of operations, and the cost of downtime grows heavier every quarter. In this new landscape, reacting is no longer enough. Teams need foresight. They need to get ahead of the issue. They need a different model entirely. This third installment centers on a simple but transformative idea. What if IT operations could finally step out of reaction mode and move into anticipation?

Detect, diagnose, and resolve network issues easily with CNM Network Health

In many organizations, developers, SREs, network engineers, and security teams work in specialized domains, which can make it hard to establish a shared view of network health. As a result, engineers often struggle to determine when a network problem that originates outside of their domain of expertise is the root cause of an incident. This lack of visibility slows investigations and delays remediation.

Driving AI ROI: How Datadog connects cost, performance, and infrastructure so you can scale responsibly

AI innovation has accelerated faster than most organizations’ ability to monitor and manage it. The shift from experimentation to production-scale workloads has driven a new class of operational challenges: rising GPU costs, opaque model performance, and the difficulty of linking spend to business value. As AI investments grow, executives need a unified way to measure efficiency and return without slowing down innovation.

Introducing Real-Time Conversations with Netdata AI

Over the past few months, we’ve seen incredible adoption of our AI Investigations and Insights reports. Teams are using them to automate the deep, thoughtful analysis required for complex post-mortems, capacity planning, and performance optimization. These comprehensive reports are fantastic when you need a well-researched, shareable document. But what about the moments during an investigation?

CTO Predictions for 2026: How AI Will Change Software Development | ShipTalk S4E7 Special Episode

In this special ShipTalk episode, host Dewan Ahmed (Principal Developer Advocate, Harness) sits down with @Harnessio Field CTO Nick Durkin for spicy—but practical—2026 predictions across AI, software delivery, DevSecOps, MLOps, and developer experience. Will we see the first “AI-caused meltdown”? Are AI “confidence scores” even trustworthy? Is 2026 the year of AI cleanup crews and recovery engineering? Nick’s take: the answer isn’t more gates—it’s guardrails, policy in the pipeline, and teams operating with the same “rulebook.”

Harness AI For Everything After Coding

AI didn’t just change how we write code. It changed everything that comes after. Application teams are shipping more code than ever with AI — but 70% of the work still happens after coding: testing, security, deployment, optimization, and keeping everything moving. As coding gets faster, delivery becomes the bottleneck. That’s where Harness comes in.