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The latest News and Information on Log Management, Log Analytics and related technologies.

Log Analysis with Machine Learning: An Automated Approach to Analyzing Logs Using ML/AI

AI log analysis helps IT teams turn massive volumes of operational data into actionable insight. By applying statistical methods, machine learning (ML), semantic analysis, and generative AI, organizations can identify unusual behavior, connect related signals, and investigate probable root causes faster. But AI-generated answers should not be mistaken for proof.

Bindplane Agent Is Here: Build, Edit, and Understand Pipelines in Plain Language

Pipeline Intelligence already recommends processors, reads live telemetry, detects log types, and generates processor bundles from natural language. But most of it lives inside a single processor node. You still have to know which one to open and what to ask for. This changes today. Bindplane Agent is your AI assistant inside Bindplane, ready to act on what you describe in plain language.

9 Best Log Management Tools and What They Cost

Most log management tools bill you on log ingestion, the volume of data you send them. That works until your log volume doubles, and the invoice doubles with it. The best log management tools let you control what gets indexed and kept, so growth stops being a budget problem. In this blog, you will see: By the end you will know which fits your volume. Log management is the full lifecycle of your log data, from the moment it is collected to the moment it is deleted.

Redact PII at the edge - and still be able to search for it

Ask a platform team why their application logs aren't in their observability backend and you'll often get a one-sentence answer: And, that's where the conversation ends. The logs stay in a silo. Or, they don't get collected at all. The team loses the troubleshooting signal, and nobody revisits the decision because the alternative looks like a compliance violation. Application logs in healthcare, aviation, insurance, and retail are full of personal information that should not be stored in plain text.

Log ingestion: you are probably paying to store logs you will never read

The default way to adopt log management is to ship everything and search it later. It is the path every vendor’s quickstart puts you on, and it is the reason log bills surprise people: ingestion is priced by volume, so“ship everything” is a spending decision disguised as a configuration default. The uncomfortable part is that most of that volume is never read. Nobody greps last Tuesday’s 200 OK access lines.

Agentic Operations Start with Context: Build the Right Data Foundation

Episode 1, "Beyond the Thread: Deconstructing the Cisco Data Fabric Powered by the Splunk Platform," explores the intersection of data strategy and operational efficiency. Hosted by Splunk's Courtney Wright, the session features insights from experts Keith McClellan and Michael Sondag on the complexities organizations face in data management and operational models.

Assisted, Augmented or Agentic? Choose Your Splunk Starting Point

Episode two of Beyond the Thread explores how organizations can leverage a solid data foundation for AI-driven actions. Hosted by Courtney Wright and featuring experts Greg Ainsley-Malik and Sonal Pardeshi, the discussion delves into the Cisco Data Fabric, powered by the Splunk platform, and its role in transforming machine data into actionable insights. The episode highlights the journey towards agentic operations, addressing the challenges faced in moving from AI-ready data to effective implementations, and examines different adoption strategies that organizations may pursue.

Log Filtering: How to Cut Log Ingest Volume Without Losing Evidence

Every log estate reaches a point where volume grows faster than the value inside it. The usual response is to find the biggest source and drop it. Cutting volume is the easy part. Cutting the right half takes judgment. Log filtering is only one of four options for an expensive source, and the other three matter just as much. In this blog, you will: By the end you can defend every rule you write, including the ones that keep data. A volume cut fails in two directions.

The pager shouldn't be what starts the investigation

Authored by Greg Janco, Engineering Manager at Mezmo I've always thought there was something backwards about incident response. An alert fires at 3 a.m. PagerDuty does its job. Somebody wakes up, grabs a laptop, connects to the VPN, opens the alert, and then starts answering the same basic questions we ask at the beginning of almost every incident. What changed? What else is broken? Have we seen this before? Some of those need a human eventually. A lot of the first pass doesn't.