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What is Logz.io?

Engineers have a deep affection for open-source solutions. We enhanced leading open-source monitoring tools like Jaeger, Prometheus, and ELK, merging them into a robust and scalable SaaS platform. This allows you to gather and analyze all your logs, metrics, traces, and additional data in a single location for comprehensive monitoring. With our user-friendly and customizable dashboards, you can easily visualize your data. Logz.io employs an AI/ML human-coach that automatically identifies and rectifies errors or exceptions in your logs. Our system can alert you via Slack, PagerDuty, Gmail, and other channels, ensuring you can swiftly address new incidents. You can centralize your metrics at any level through our Prometheus-as-a-service offering. By unifying logs and traces, we simplify the monitoring process. Getting started is easy—just add three lines of code to your Prometheus configuration file to initiate the forwarding of your metrics and data to Logz.io, streamlining your monitoring experience even further. This integration ultimately enhances your operational efficiency and response times.

What is IBM Log Analysis?

Leveraging log services is crucial, especially when teams seek insights at the cluster level. Boost operational efficiency and uncover deeper insights with the IBM® Log Analysis service, known for its seamless compatibility with various cloud-native runtimes and environments. This service provides an array of features, including log collection, log tailing, and fast log searches tailored to your needs. Users can take advantage of natural language queries and enjoy a search retention period that lasts up to 30 days. Moreover, you can implement cluster-level logging for Kubernetes clusters, granting access to a diverse range of logs such as worker, pod, application, and network logs. This information can be monitored from multiple sources, enabling the centralized management of Ubuntu logs on the IBM Cloud®. DevOps teams are empowered to archive logs directly from an IBM Log Analysis instance into a bucket within an IBM Cloud Object Storage instance, streamlining data handling. By consolidating all log data in one centralized hub, you can ensure compatibility with services such as Pager Duty, Slack, webhooks, and more. With support for over 30 integrations and ingestion sources, along with the benefits of natural language queries and a pay-per-GB pricing model, this holistic approach not only simplifies the management of logs but also enables teams to quickly derive actionable insights. In this way, organizations can enhance their operational capabilities and respond more effectively to system events.

Media

Media

Integrations Supported

Kubernetes
AWS AppFabric
AlertOps
Amazon Web Services (AWS)
Apache Kafka
Check Point IPS
Check Point Infinity
Docker
Google Cloud Platform
Lightrun
Microsoft Azure
Node.js
Observo AI
PagerDuty
Redis
Shift
Squadcast

Integrations Supported

Kubernetes
IBM Cloud
IBM Cloud Object Storage

API Availability

API Availability

Pricing Information

$89 per month
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Logz.io

Date Founded

2015

Company Location

Israel

Company Website

logz.io

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/cloud/log-analysis

Categories and Features

Cloud Monitoring

Not specified

Log Analysis

Not specified

Log Management

Archiving
Compliance Reporting
Data Visualization
Event Logs
Syslogs
Web Logs

Log Monitoring

Not specified

Observability

Not specified

SIEM

Not specified

Categories and Features

Log Analysis

Not specified

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