Alternatives to AWS CloudTrail logo

Alternatives to AWS CloudTrail

AWS Config, AWS X-Ray, Splunk, Logstash, and Logback are the most popular alternatives and competitors to AWS CloudTrail.
332
245
+ 1
14

What is AWS CloudTrail and what are its top alternatives?

With CloudTrail, you can get a history of AWS API calls for your account, including API calls made via the AWS Management Console, AWS SDKs, command line tools, and higher-level AWS services (such as AWS CloudFormation). The AWS API call history produced by CloudTrail enables security analysis, resource change tracking, and compliance auditing. The recorded information includes the identity of the API caller, the time of the API call, the source IP address of the API caller, the request parameters, and the response elements returned by the AWS service.
AWS CloudTrail is a tool in the Log Management category of a tech stack.

Top Alternatives to AWS CloudTrail

  • AWS Config
    AWS Config

    AWS Config is a fully managed service that provides you with an AWS resource inventory, configuration history, and configuration change notifications to enable security and governance. With AWS Config you can discover existing AWS resources, export a complete inventory of your AWS resources with all configuration details, and determine how a resource was configured at any point in time. These capabilities enable compliance auditing, security analysis, resource change tracking, and troubleshooting. ...

  • AWS X-Ray
    AWS X-Ray

    It helps developers analyze and debug production, distributed applications, such as those built using a microservices architecture. With this, you can understand how your application and its underlying services are performing to identify and troubleshoot the root cause of performance issues and errors. It provides an end-to-end view of requests as they travel through your application, and shows a map of your application’s underlying components. ...

  • Splunk
    Splunk

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

  • 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. ...

  • 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. ...

  • 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. ...

  • Serilog
    Serilog

    It provides diagnostic logging to files, the console, and elsewhere. It is easy to set up, has a clean API, and is portable between recent .NET platforms. ...

  • 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. ...

AWS CloudTrail alternatives & related posts

AWS Config logo

AWS Config

52
87
6
Config gives you a detailed inventory of your AWS resources and their current configuration, and continuously records configuration...
52
87
+ 1
6
PROS OF AWS CONFIG
  • 4
    Backed by Amazon
  • 2
    One stop solution
CONS OF AWS CONFIG
  • 1
    Not user friendly

related AWS Config posts

AWS X-Ray logo

AWS X-Ray

62
105
0
An application performance management service
62
105
+ 1
0
PROS OF AWS X-RAY
    Be the first to leave a pro
    CONS OF AWS X-RAY
      Be the first to leave a con

      related AWS X-Ray posts

      Splunk logo

      Splunk

      527
      852
      13
      Search, monitor, analyze and visualize machine data
      527
      852
      + 1
      13
      PROS OF SPLUNK
      • 2
        Alert system based on custom query results
      • 2
        API for searching logs, running reports
      • 2
        Query engine supports joining, aggregation, stats, etc
      • 1
        Ability to style search results into reports
      • 1
        Query any log as key-value pairs
      • 1
        Splunk language supports string, date manip, math, etc
      • 1
        Granular scheduling and time window support
      • 1
        Custom log parsing as well as automatic parsing
      • 1
        Dashboarding on any log contents
      • 1
        Rich GUI for searching live logs
      CONS OF SPLUNK
      • 1
        Splunk query language rich so lots to learn

      related Splunk posts

      Shared insights
      on
      KibanaKibanaSplunkSplunkGrafanaGrafana

      I use Kibana because it ships with the ELK stack. I don't find it as powerful as Splunk however it is light years above grepping through log files. We previously used Grafana but found it to be annoying to maintain a separate tool outside of the ELK stack. We were able to get everything we needed from Kibana.

      See more
      Logstash logo

      Logstash

      9.7K
      7.3K
      102
      Collect, Parse, & Enrich Data
      9.7K
      7.3K
      + 1
      102
      PROS OF LOGSTASH
      • 68
        Free
      • 18
        Easy but powerful filtering
      • 12
        Scalable
      • 2
        Kibana provides machine learning based analytics to log
      • 1
        Great to meet GDPR goals
      • 1
        Well Documented
      CONS OF LOGSTASH
      • 4
        Memory-intensive
      • 1
        Documentation difficult to use

      related Logstash posts

      Tymoteusz Paul
      Devops guy at X20X Development LTD · | 23 upvotes · 5.3M views

      Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

      It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

      I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

      We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

      If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

      The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

      Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

      See more
      Tanya Bragin
      Product Lead, Observability at Elastic · | 10 upvotes · 665K views

      ELK Stack (Elasticsearch, Logstash, Kibana) is widely known as the de facto way to centralize logs from operational systems. The assumption is that Elasticsearch (a "search engine") is a good place to put text-based logs for the purposes of free-text search. And indeed, simply searching text-based logs for the word "error" or filtering logs based on a set of a well-known tags is extremely powerful, and is often where most users start.

      See more
      Logback logo

      Logback

      1.3K
      58
      0
      A logging framework for Java applications
      1.3K
      58
      + 1
      0
      PROS OF LOGBACK
        Be the first to leave a pro
        CONS OF LOGBACK
          Be the first to leave a con

          related Logback posts

          SLF4J logo

          SLF4J

          1.1K
          53
          0
          Simple logging facade for Java
          1.1K
          53
          + 1
          0
          PROS OF SLF4J
            Be the first to leave a pro
            CONS OF SLF4J
              Be the first to leave a con

              related SLF4J posts

              Serilog logo

              Serilog

              1.1K
              84
              0
              A portable and structured logging framework to record diagnostic logs
              1.1K
              84
              + 1
              0
              PROS OF SERILOG
                Be the first to leave a pro
                CONS OF SERILOG
                  Be the first to leave a con

                  related Serilog posts

                  ELK logo

                  ELK

                  734
                  776
                  20
                  The acronym for three open source projects: Elasticsearch, Logstash, and Kibana
                  734
                  776
                  + 1
                  20
                  PROS OF ELK
                  • 13
                    Open source
                  • 3
                    Good for startups with monetary limitations
                  • 2
                    Can run locally
                  • 1
                    Easy to setup
                  • 1
                    External Network Goes Down You Aren't Without Logging
                  • 0
                    Json log supprt
                  • 0
                    Live logging
                  CONS OF ELK
                  • 4
                    Elastic Search is a resource hog
                  • 3
                    Logstash configuration is a pain
                  • 1
                    Bad for startups with personal limitations

                  related ELK posts

                  Wallace Alves
                  Cyber Security Analyst · | 1 upvote · 652.2K views

                  Docker Docker Compose Portainer ELK Elasticsearch Kibana Logstash nginx

                  See more