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Jun 8, 2022   |  By Ranjan
Full-stack observability is a term that you may have heard being tossed around in many conversations on the topic of observability. What does it mean? Full-stack observability constitutes having visibility into all layers of your technology stack. Collecting, correlating, and aggregating all telemetry in the components provides insight into the behavior, performance, and health of the system.
May 12, 2022   |  By Tito George
Observability data has three types: metrics, traces, and logs. In this article, we will look at how anomaly detection techniques can be applied to time-series metrics for observability use cases. There are many different anomaly detection algorithms, but they all share a common goal: to find data points that are significantly different from the rest of the data. This can be useful for identifying outliers, monitoring for unusual behavior, and detecting errors in data collection.
May 11, 2022   |  By Ranjan
If you’re using an observability stack, chances are you’re familiar with alerting. Alerts help users get notified when something interesting happens that they need to act on. Alerting comes with its challenges when too many alerts become a problem and not the solution. Is your team stuck with alert fatigue? It is a very real problem, and it’s not uncommon for observability solutions to generate false alerts.
May 10, 2022   |  By Ranjan
Businesses everywhere are going through digital transformation. This means that they are adapting their operations and strategies to better compete in the digital age. A key part of this transformation is better managing the large volumes of machine data generated every day. Machine data management can be complex, but with the help of a machine data fabric, organizations can tame these complexities and successfully scale their challenges.
Mar 30, 2022   |  By Ranjan
Prometheus is a wildly deployed open source monitoring system for time series metrics. For observability use cases, it is important to bring together logs and metrics for root cause analysis into a tightly integrated framework to help faster root cause. A Prometheus deployment is configured with scrape targets from which metrics are collected periodically. The data is stored in a multi-dimensional data model with metric data stored along with a set of key-value pairs, commonly referred to as labels.
Feb 21, 2022   |  By Ajit Chelat
Metrics are the primary means of representing your system’s general health and any other valuable information for monitoring, alerting, and observability. Despite the Kubernetes ecosystem growing by the day, the community continues to rely on particular technologies to ease operation workloads. One of them is Prometheus. Prometheus bridges the gap between monitoring and alerting.
Feb 18, 2022   |  By Ajit Chelat
For all the productivity gains created by DevOps, there’s a nasty side effect. Short release cycles, lots of infrastructure changes, and developer-driven changes to live environments make for a recipe for frequent production issues. When problems occur, developers are being pulled to troubleshoot, which can be painful. Have you ever been on a production server and needed to troubleshoot an issue? Maybe there is an NGINX error or a 700 error from your Redis store.
Feb 16, 2022   |  By Ajit Chelat
In late 2021 we kick started a project with a customer who had shown an interest in reducing log ingestion costs and reached out to us via Linkedin. Like many others, this customer had a combination of popular logging platforms in place that were built and put together for various reasons over time. No real reason why, just different departments, skills, tooling budgets and business needs influenced their position.
Feb 4, 2022   |  By Ajit Chelat
It’s likely that you already know how helpful logs can be in analyzing the inner workings of your IT environments. Beyond that, you may be familiar with the concept of using log data for debugging issues, identifying threats, or gaining context of performance bottlenecks. Log data from a single data source can fulfill a variety of use cases.
Feb 2, 2022   |  By Ajit Chelat
In January, the LOGIQ.AI team shipped plenty of new features, enhanced existing ones, and squashed a few bugs to make your full-stack observability and data pipeline control and storage experience using the LOGIQ.AI platform better than ever before. This blog captures the key features and enhancements we pushed last month.
Apr 2, 2022   |  By LOGIQ
The timely root cause of issues can be hard with different representations of data streams. LOGIQ.AI makes it easy to bring together logs and time-series data into a simple root cause workflow where time-series data can be mapped to your log streams in real-time.
Feb 15, 2022   |  By LOGIQ
This video takes you through logging into LogFlow using an invite and changing your temporary password
Feb 15, 2022   |  By LOGIQ
This video shows how you can create new user accounts as a LogFlow administrator.
Feb 15, 2022   |  By LOGIQ
In this video, you'll learn how to create user groups to delegate access within LogFlow.
Nov 26, 2021   |  By LOGIQ
In this video, we'll demonstrate how you can leverage LogFlow's rewrite rules to identify patterns of sensitive information in your log data streams and replace or rewrite them for better data security and compliance.
Nov 26, 2021   |  By LOGIQ
Introducing LogFlow Rule Packs - built-in rule sets for common customer environments and workflows that enable you to tag, rewrite, filter, and extract data from incoming data streams. LogFlow Rule Packs also includes built-in SIEM rules that help you augment incoming data with security events.
Nov 2, 2021   |  By LOGIQ
LogFlow enables on-demand replay of data for any time range from InstaStore to a target system of your choice.
Oct 25, 2021   |  By LOGIQ
In this video, you'll learn how to create a forwarder within LogFlow to forward data to an Elastic index.
Oct 22, 2021   |  By LOGIQ
Send application logs to Splunk using LogFlow
Oct 22, 2021   |  By LOGIQ
Create LogFlow forwarder for Splunk HTTP Event Collector
Apr 11, 2022   |  By LOGIQ
Kubernetes is one of the leaders in the container orchestration market. A recent survey by Cloud Native Computing Foundation (CNCF) suggests that 84% of companies are running Kubernetes containers in production. However, organizations running Kubernetes have also reported severe security threats in their respective container environment, with each threat linked to the container's lifecycle phase. These organizations often have to remediate vulnerabilities during the development phases and respond to threats during runtime to keep the impact to production and downtimes at a minimum.
Apr 11, 2022   |  By LOGIQ
Kubernetes is an open-source container orchestration platform designed to run distributed services and applications at scale. A K8s or Kubernetes cluster contains several components that are a part of either the Kubernetes control plane or Kubernetes nodes. Over the years, Kubernetes has emerged as the hot topic in the DevOps space and is among the most wanted platforms for developers. As they are widely adopted to support varied use cases, cluster security is becoming a big concern for many organizations.
Apr 1, 2022   |  By LOGIQ
Kubernetes automates the application life cycle! But, how do you configure roles, capabilities, and control access rights in Kubernetes? The goal of this guide is to show how you can secure a Kubernetes cluster using Roles Based Access Control (RBAC), Network Policies, and Runtime Privileges for maximum control and data privacy.

We are the only platform that provides seamless routing, with an attached infinite data reservoir, while providing both sequential, random access and indexed search on your data streams.

By unifying data types, such as logs, metrics, databases, and APIs, LOGIQ’s Observability platform enables you to harness the power of machine data analytics for applications and infrastructure on a single platform, with 1-Click simplicity. Users can aggregate log data, gather performance metrics, access API’s and connect databases such as Elastic, Mongo, Postgres, Druid, and MySQL for real-time visibility into the health of their IT infrastructure and application environments.

Centralized control for all your observability data:

  • Log Management: Stream and analyze logs across your applications and infrastructure in real-time, generate quick and insightful visualizations from log data, and troubleshoot issues with AI and ML-driven analytics at any scale.
  • API Observability: Analyze all your APIs, identify patterns and behavior that help you troubleshoot issues, prevent threats preemptively, understand API usage, and confidently ship great APIs.
  • App & Infra Monitoring: LOGIQ’s Prometheus-backed, monitoring engine generates insightful metrics that let you monitor the health and performance of all your applications and infrastructure and troubleshoot anomalies at scale.
  • Integrated SIEM & SOAR: Leverage LOGIQ’s built-in SIEM rules engine to detect anomalous security events in real-time and at an infinite scale. Sample security events in log data against crowdsourced security rules from the Sigma project for faster threat detection.

Observability Data Pipeline as a Service.