What is logz.io and what are its top alternatives?
Logz.io is a cloud-based log management platform that offers log analysis, monitoring, and visualization tools for DevOps teams. It features real-time monitoring, machine learning capabilities for anomaly detection, and integrations with popular tools like Elasticsearch and Kibana. However, some limitations include the high cost for larger amounts of data, limited customization options, and potential learning curve for new users.
Elasticsearch: Elasticsearch is an open-source search and analytics engine that can be used for log management and analysis. Key features include real-time search, scalability, and a range of plugins for data visualization and monitoring. Pros include open-source nature, scalability, and customization options. Cons include potentially higher complexity for beginners and higher maintenance overhead compared to a managed service like Logz.io.
Splunk: Splunk is a popular log management and analysis platform that offers powerful search capabilities, visualizations, and machine learning features. Pros include a robust query language, extensive integrations, and a large user community. Cons include high costs for large volumes of data and potential complexity in setting up and configuring the system.
Sumo Logic: Sumo Logic is a cloud-based log management platform that provides real-time analytics, troubleshooting tools, and scalability for large-scale log data. Key features include auto-scaling, machine learning algorithms, and pre-built dashboards. Pros include ease of use, scalability, and strong security features. Cons include potential cost for larger data volumes and less customization compared to self-hosted solutions.
Datadog: Datadog is a monitoring and analytics platform that offers log management capabilities alongside other monitoring tools. Key features include real-time log search, analytics, and visualization. Pros include seamless integration with other monitoring tools, ease of use, and a unified platform for monitoring and log management. Cons include potential cost for larger data volumes and limited customization options for log analysis.
Loggly: Loggly is a cloud-based log management service that offers real-time log analysis, visualization, and alerting features. Key features include dynamic field support, scalable architecture, and integrations with popular tools like Slack and PagerDuty. Pros include ease of use, scalability, and strong search capabilities. Cons include potential cost for larger data volumes and limited customization options compared to self-hosted solutions.
Graylog: Graylog is an open-source log management platform that offers log analysis, search, and visualization tools. Key features include real-time log monitoring, alerts, and dashboards. Pros include open-source nature, customization options, and strong community support. Cons include potentially higher complexity for beginners and higher maintenance overhead compared to a managed service like Logz.io.
LogDNA: LogDNA is a cloud-based log management platform that offers real-time log analysis, monitoring, and alerting capabilities. Key features include easy setup, custom parsing rules, and integrations with popular tools like Slack and Jira. Pros include ease of use, scalability, and competitive pricing. Cons include potential cost for larger data volumes and limited customization options compared to self-hosted solutions.
Papertrail: Papertrail is a cloud-based log management service that provides real-time log search, monitoring, and archiving features. Key features include simple setup, fast log searching, and integrations with popular tools like Heroku and AWS. Pros include ease of use, competitive pricing, and unlimited data retention. Cons include potential limitations in complex log analysis and search capabilities compared to more advanced tools like Logz.io.
Logz.io Open Source Alternative: For those looking for an open-source alternative to Logz.io, tools like Superset offer log management, visualization, and analysis capabilities. Key features include dashboard creation, SQL querying, and integration with popular databases like MySQL and PostgreSQL. Pros include open-source nature, customization options, and community support. Cons include potentially higher complexity for beginners and self-hosting requirements compared to a managed service like Logz.io.
Coralogix: Coralogix is a cloud-based log management platform that offers real-time log analytics, monitoring, and anomaly detection. Key features include machine learning algorithms, automatic log parsing, and integrations with popular tools like Kubernetes and Slack. Pros include ease of use, competitive pricing, and strong anomaly detection capabilities. Cons include potential cost for larger data volumes and limited customization options compared to self-hosted solutions.
Top Alternatives to logz.io
- Loggly
It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain. ...
- Logentries
Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users. ...
- Coralogix
Coralogix is a stateful streaming data platform that provides real-time insights and long-term trend analysis with no reliance on storage or indexing, solving the monitoring challenges of data growth in large-scale systems. ...
- Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data. ...
- Kibana
Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch. ...
- Elastic Cloud
A growing family of Elastic SaaS offerings that make it easy to deploy, operate, and scale Elastic products and solutions in the cloud. From an easy-to-use hosted and managed Elasticsearch experience to powerful, out-of-the-box search solutions. ...
- 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. ...
- Graylog
Centralize and aggregate all your log files for 100% visibility. Use our powerful query language to search through terabytes of log data to discover and analyze important information. ...
logz.io alternatives & related posts
- Centralized log management37
- Easy to setup25
- Great filtering21
- Live logging16
- Json log support15
- Log Management10
- Alerting10
- Great Dashboards7
- Love the product7
- Heroku Add-on4
- Easy to setup and use2
- Easy setup2
- No alerts in free plan2
- Great UI2
- Good parsing2
- Powerful2
- Fast search2
- Backup to S32
- Pricey after free plan3
related Loggly posts
- Log search34
- Live logs27
- Easy setup19
- Heroku Add-on14
- Backup to S35
- Easy setup, independent of existing logging setup2
- Free2
- Search/query with regex2
- E0
related Logentries posts
Regarding Continuous Integration - we've started with something very easy to set up - CircleCI , but with time we're adding more & more complex pipelines - we use Jenkins to configure & run those. It's much more effort, but at some point we had to pay for the flexibility we expected. Our source code version control is Git (which probably doesn't require a rationale these days) and we keep repos in GitHub - since the very beginning & we never considered moving out. Our primary monitoring these days is in New Relic (Ruby & SPA apps) and AppSignal (Elixir apps) - we're considering unifying it in New Relic , but this will require some improvements in Elixir app observability. For error reporting we use Sentry (a very popular choice in this class) & we collect our distributed logs using Logentries (to avoid semi-manual handling here).
Logentries, LogDNA, Timber.io, Papertrail and Sumo Logic provide free pricing plan for #Heroku application. You can add these applications as add-ons very easily.
related Coralogix posts
- API for searching logs, running reports3
- Alert system based on custom query results3
- Splunk language supports string, date manip, math, etc2
- Dashboarding on any log contents2
- Custom log parsing as well as automatic parsing2
- Query engine supports joining, aggregation, stats, etc2
- Rich GUI for searching live logs2
- Ability to style search results into reports2
- Granular scheduling and time window support1
- Query any log as key-value pairs1
- Splunk query language rich so lots to learn1
related Splunk posts
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.
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.
- Easy to setup88
- Free65
- Can search text45
- Has pie chart21
- X-axis is not restricted to timestamp13
- Easy queries and is a good way to view logs9
- Supports Plugins6
- Dev Tools4
- More "user-friendly"3
- Can build dashboards3
- Out-of-Box Dashboards/Analytics for Metrics/Heartbeat2
- Easy to drill-down2
- Up and running1
- Unintuituve7
- Works on top of elastic only4
- Elasticsearch is huge4
- Hardweight UI3
related Kibana posts
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.
This is my stack in Application & Data
JavaScript PHP HTML5 jQuery Redis Amazon EC2 Ubuntu Sass Vue.js Firebase Laravel Lumen Amazon RDS GraphQL MariaDB
My Utilities Tools
Google Analytics Postman Elasticsearch
My Devops Tools
Git GitHub GitLab npm Visual Studio Code Kibana Sentry BrowserStack
My Business Tools
Slack
related Elastic Cloud posts
I wonder what the best option for hosting my home page https://www.sireus.se is? On Jelastic or Elastic Cloud? Which host is the most suitable and cost-effective?
- Open source14
- Can run locally4
- Good for startups with monetary limitations3
- External Network Goes Down You Aren't Without Logging1
- Easy to setup1
- Json log supprt0
- Live logging0
- Elastic Search is a resource hog5
- Logstash configuration is a pain3
- Bad for startups with personal limitations1
related ELK posts
Docker Docker Compose Portainer ELK Elasticsearch Kibana Logstash nginx
- Open source19
- Powerfull13
- Well documented8
- Alerts6
- User authentification5
- Flexibel query and parsing language5
- Alerts and dashboards3
- User management3
- Easy query language and english parsing3
- Easy to install2
- Manage users and permissions1
- A large community1
- Free Version1
- Does not handle frozen indices at all1