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Splunk

Splunk

#25in Databases
Stacks621Discussions5
Followers1.02k
OverviewDiscussions5

What is Splunk?

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

Splunk is a tool in the Databases category of a tech stack.

Key Features

Predict and prevent problems with one unified monitoring experienceStreamline your entire security stack with Splunk as the nerve centerDetect, investigate and diagnose problems easily with end-to-end observability

Splunk Pros & Cons

Pros of Splunk

  • ✓Alert system based on custom query results
  • ✓API for searching logs, running reports
  • ✓Ability to style search results into reports
  • ✓Custom log parsing as well as automatic parsing
  • ✓Dashboarding on any log contents
  • ✓Query engine supports joining, aggregation, stats, etc
  • ✓Rich GUI for searching live logs
  • ✓Splunk language supports string, date manip, math, etc
  • ✓Granular scheduling and time window support
  • ✓Query any log as key-value pairs

Cons of Splunk

  • ✗Splunk query language rich so lots to learn

Splunk Alternatives & Comparisons

What are some alternatives to Splunk?

Logstash

Logstash

Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.

Apache Spark

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

SLF4J

SLF4J

It is a simple Logging Facade for Java (SLF4J) serves as a simple facade or abstraction for various logging frameworks allowing the end user to plug in the desired logging framework at deployment time.

Logback

Logback

It is intended as a successor to the popular log4j project. It is divided into three modules, logback-core, logback-classic and logback-access. The logback-core module lays the groundwork for the other two modules, logback-classic natively implements the SLF4J API so that you can readily switch back and forth between logback and other logging frameworks and logback-access module integrates with Servlet containers, such as Tomcat and Jetty, to provide HTTP-access log functionality.

ELK

ELK

It is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.

Papertrail

Papertrail

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.

Splunk Integrations

Google Anthos, Catchpoint Synthetics, Cloudmarker, OverOps, Amazon GuardDuty and 7 more are some of the popular tools that integrate with Splunk. Here's a list of all 12 tools that integrate with Splunk.

Google Anthos
Google Anthos
Catchpoint Synthetics
Catchpoint Synthetics
Cloudmarker
Cloudmarker
OverOps
OverOps
Amazon GuardDuty
Amazon GuardDuty
Rsyslog
Rsyslog
Wazuh
Wazuh
AlienVault
AlienVault
Resilio
Resilio
AlertOps
AlertOps
Squadcast
Squadcast
Rafay Systems
Rafay Systems

Splunk Discussions

Discover why developers choose Splunk. Read real-world technical decisions and stack choices from the StackShare community.Showing 3 of 5 discussions.

Jai Soma
Jai Soma

Jan 10, 2023

Needs adviceonElasticsearchElasticsearchSplunkSplunk

We are currently exploring Elasticsearch and Splunk for our centralized logging solution. I need some feedback about these two tools. We expect our logs in the range of upwards > of 10TB of logging data.

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VenD
VenD

Jan 16, 2022

Needs adviceonDjangoDjangoSplunkSplunk

I am designing a Django application for my organization which will be used as an internal tool. The infra team said that I will not be having SSH access to the production server and I will have to log all my backend application messages to Splunk. I have no knowledge of Splunk so the following are the approaches I am considering: Approach 1: Create an hourly cron job that uploads the server log file to some Splunk storage for later analysis. - Is this possible? Approach 2: Is it possible just to stream the logs to some splunk endpoint? (If yes, I feel network usage and communication overhead will be a pain-point for my application)

Is there any better or standard approach? Thanks in advance.

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Marina Ripper
Marina Ripper

Cellere

Apr 26, 2021

Needs adviceonSplunkSplunk

I am using Splunk, but trying to change to an open-source software; what I need is something that reads in "real-time" an archive, it's not exactly a log, it's actually data itself (there is a lot of data, by the way), stores this data/log for a long time (more than 2 years), has a pretty easy way to search the data read (so some search language where I can search by IP for example), and a way to connect to the software, where I can search by API.

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