Alternatives to Changefeed logo

Alternatives to Changefeed

InVision, Intercom, Logstash, Papertrail, and ELK are the most popular alternatives and competitors to Changefeed.
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What is Changefeed and what are its top alternatives?

It makes it easy to keep and manage a changelog for your products. Keep your users up to date and engaged with every update your team ships.
Changefeed is a tool in the Engagement/Lifecycle Marketing category of a tech stack.

Top Alternatives of Changefeed

Changefeed alternatives & related posts

related InVision posts

Priit Kaasik
Priit Kaasik
Engineering Lead at Katana MRP | 8 upvotes 279.6K views
atKatana MRPKatana MRP
Confluence
Confluence
Bitbucket
Bitbucket
GitHub
GitHub
Jira
Jira
Microsoft Office 365
Microsoft Office 365
Slack
Slack
InVision
InVision
Sketch
Sketch

How we ended up choosing Confluence as our internal web / wiki / documentation platform at Katana.

It happened because we chose Bitbucket over GitHub . We had Katana's first hackaton to assemble and test product engineering platform. It turned out that at that time you could have Bitbucket's private repositories and a team of five people for free - Done!

This decision led us to using Bitbucket pipelines for CI, Jira for Kanban, and finally, Confluence. We also use Microsoft Office 365 and started with using OneNote, but SharePoint is still a nightmare product to use to collaborate, so OneNote had to go.

Now, when thinking of the key value of Confluence to Katana then it is Product Requirements Management. We use Page Properties macros, integrations (with Slack , InVision, Sketch etc.) to manage Product Roadmap, flash out Epic and User Stories.

We ended up with using Confluence because it is the best fit for our current engineering ecosystem.

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related Intercom posts

Kirill Shirinkin
Kirill Shirinkin
Cloud and DevOps Consultant at mkdev | 12 upvotes 513.8K views
atmkdevmkdev
Trello
Trello
Slack
Slack
Basecamp
Basecamp
Intercom
Intercom
Mailchimp
Mailchimp
Stripe
Stripe
Rollbar
Rollbar
GitLab
GitLab
G Suite
G Suite

As a small startup we are very conscious about picking up the tools we use to run the project. After suffering with a mess of using at the same time Trello , Slack , Telegram and what not, we arrived at a small set of tools that cover all our current needs. For product management, file sharing, team communication etc we chose Basecamp and couldn't be more happy about it. For Customer Support and Sales Intercom works amazingly well. We are using MailChimp for email marketing since over 4 years and it still covers all our needs. Then on payment side combination of Stripe and Octobat helps us to process all the payments and generate compliant invoices. On techie side we use Rollbar and GitLab (for both code and CI). For corporate email we picked G Suite. That all costs us in total around 300$ a month, which is quite okay.

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Priit Kaasik
Priit Kaasik
Engineering Lead at Katana MRP | 7 upvotes 28.1K views
atKatana MRPKatana MRP
JavaScript
JavaScript
Appcues
Appcues
Intercom
Intercom
Hotjar
Hotjar
Amazon CloudFront
Amazon CloudFront
Amazon S3
Amazon S3
Heroku
Heroku
Elevio
Elevio
#Ad-blocking

Sometimes #ad-blocking addons can cause a real headache when working with JavaScript apps. Onboarding assistants (Appcues + elevio ), chat (Intercom) and product usage insight (Hotjar) have all landed on their blacklists. I guess there is a perfectly good reason for this that I just don't know.

In order to fix this, we had to set up our own content delivery service. We chose Amazon CloudFront and Amazon S3 to do the job because it has a good synergy with Heroku PaaS we are already using.

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Logstash logo

Logstash

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Collect, Parse, & Enrich Data
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Logstash
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Changefeed

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Tymoteusz Paul
Tymoteusz Paul
Devops guy at X20X Development LTD | 21 upvotes 1.7M views
Vagrant
Vagrant
VirtualBox
VirtualBox
Ansible
Ansible
Elasticsearch
Elasticsearch
Kibana
Kibana
Logstash
Logstash
TeamCity
TeamCity
Jenkins
Jenkins
Slack
Slack
Apache Maven
Apache Maven
Vault
Vault
Git
Git
Docker
Docker
CircleCI
CircleCI
LXC
LXC
Amazon EC2
Amazon EC2

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.

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Tanya Bragin
Tanya Bragin
Product Lead, Observability at Elastic | 10 upvotes 374.7K views
atElasticElastic
Elasticsearch
Elasticsearch
Logstash
Logstash
Kibana
Kibana

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.

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related Papertrail posts

Logentries
Logentries
LogDNA
LogDNA
Timber.io
Timber.io
Papertrail
Papertrail
Sumo Logic
Sumo Logic
#Heroku

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.

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ELK

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The acronym for three open source projects: Elasticsearch, Logstash, and Kibana
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    related ELK posts

    Wallace Alves
    Wallace Alves
    Cyber Security Analyst | 1 upvotes 241.3K views
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    nginx

    Docker Docker Compose Portainer ELK Elasticsearch Kibana Logstash nginx

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    Freshchat

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    Turn visitors into leads and customers into happy users
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      Changefeed
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      Fluentd

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      Unified logging layer
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      Fluentd
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