You can look out for Prometheus Instrumentation (https://prometheus.io/docs/practices/instrumentation/) Client Library available in various languages https://prometheus.io/docs/instrumenting/clientlibs/ to create the custom metric you need for AS4000 and then Grafana can query the newly instrumented metric to show on the dashboard.

Can't say anything to Sysdig. I clearly prefer Datadog as

• they provide plenty of easy to "switch-on" plugins for various technologies (incl. most of AWS)
• easy to code (python) agent plugins / api for own metrics
• brillant dashboarding / alarms with many customization options
• pricing is OK, there are cheaper options for specific use cases but if you want superior dashboarding / alarms I haven't seen a good competitor (despite your own Prometheus / Grafana / Kibana dog food)

IMHO NewRelic is "promising since years" ;) good ideas but bad integration between their products. Their Dashboard query language is really nice but lacks critical functions like multiple data sets or advanced calculations. Needless to say you get all of that with Datadog.

Need help setting up a monitoring / logging / alarm infrastructure? Send me a message!

Hi Medeti,

you are right. Building based on your stack something with open source is heavy lifting. A lot of people I know start with such a set-up, but quickly run into frustration as they need to dedicated their best people to build a monitoring which is doing the job in a professional way.

As you are microservice focussed and are looking for 'low implementation and maintenance effort', you might want to have a look at INSTANA, which was built with modern tool stacks in mind. https://www.instana.com/apm-for-microservices/

We have a public sand-box available if you just want to have a look at the product once and of course also a free-trial: https://www.instana.com/getting-started-with-apm/

Let me know if you need anything on top.

I have hands on production experience both with New Relic and Datadog. I personally prefer Datadog over NewRelic because of the UI, the Documentation and the overall user/developer experience.

NewRelic however, can do basically the same things as Datadog can, and some of the features like alerting have been present in NewRelic for longer than in Datadog. The cool thing about NewRelic is their last-summer-updated pricing: you no longer pay per host but after data you send towards New Relic. This can be a huge cost saver depending on your particular setup

https://docs.newrelic.com/docs/accounts/accounts-billing/new-relic-one-pricing-billing/new-relic-one-pricing-billing

I'd go for Datadog, but given you have lots of containers I would also make a cost calculation. If the price difference is significant and there's a budget constraint NewRelic might be the better choice.

If you're already using Prometheus for your system metrics, then it seems like standing up Elasticsearch just for Linux host monitoring is excessive. The node_exporter is probably sufficient if you'e looking for standard system metrics.

Another thing to consider is that Metricbeat / ELK use a push model for metrics delivery, whereas Prometheus pulls metrics from each node it is monitoring. Depending on how you manage your network security, opting for one solution over two may make things simpler.

Hi Sunil! Unfortunately, I don´t have much experience with Metricbeat so I can´t advise on the diffs with Prometheus...for Linux server, I encourage you to use Prometheus node exporter and for PCF, I would recommend using the instana tile (https://www.instana.com/supported-technologies/pivotal-cloud-foundry/). Let me know if you have further questions! Regards Jose

I work at Volvo Car Corporation as a consultant Project Manager. We have deployed Zabbix in all of our factories for factory monitoring because after thorough investigation we saw that Zabbix supports the wide variety of Operating Systems, hardware peripherals and devices a Car Manufacturer has.

No other tool had the same amount of support onboard for our production environment and we didn't want to end up using a different tool again for several areas. That is the major strong point about Zabbix and it's free of course. Another strong point is the documentation which is widely available; Zabbix Youtube channel with tutorial video's, Zabbix share which holds free templates, the Zabbix online documentation and the Zabbix forum also helped us out quite a bit. Deployment is quite easy since it uses templates, so almost all configuration can be done on server side.

To conclude, we are really pleased with the tool so far, it helped us detect several causes of issues that were a pain to solve in the past.

Centreon is part of the Nagios ecosystem, meaning there is a huge number of resources you may find around in the community (plugins, skills, addons). Zabbix monitoring paradigms are totally different from Centreon. Centreon plugins have some kind of intelligence when they are launched, where Zabbix monitoring rules are configured centrally with the raw data collected. Testing both will help you understand :) Users used to say Centreon may be faster for setup and deployment. And in the end, both are full of monitoring features. Centreon has out of the box a full catalog of probes from cloud to the edge https://www.centreon.com/en/plugins-pack-list/ As soon as you have defined your monitoring policies and template, you can deploy it fast through command line API or REST API. Centreon plays well in the ITSM, Automation, AIOps spaces with many connectors for Prometheus, ServiceNow, GLPI, Ansible, Chef, Splunk, ... The polling server mode is one of the differentiators with Centreon. You set up remote server(s) and chose btw multiple information-exchange mechanisms. Powerful and resilient for remote, VPN, DMZ, satellite networks. Centreon is a good value for price to do a data collection (availability, performance, fault) on a wide range of technologies (physical, legacy, cloud). There are pro support and enterprise version with dashboards and reporting. IT Central Station gathers many user feedback you can rely on both Centreon & Zabbix https://www.itcentralstation.com/products/centreon-reviews  

We highly recommend Zabbix. We have used it to build our own monitoring product (available on cloud -like datadog- or on premise with support) because of its flexibility and extendability. It can be easily integrated with the powerful dashboarding and data aggregation of Grafana, so it is perfect. All configuration is done via web and templates, so it scales well and can be distributed via proxies. I think there also more companies providing consultancy in Zabbix (like ours) than Centreon and community is much wider. Also Zabbix roadmap and focus (compatibility with Elasticsearch, Prometheus, TimescaleDB) is really really good.

Hi Vivek, what's your stack? If huge monitoring bills are your concern and if you’re using a number of JVM languages, or mostly Scala / Akka, and would like “one tool to monitor them all”, Kamon might be the friendliest choice to go for.

Kamon APM’s major benefit is it comes with a built-in dashboard for the most important metrics to monitor, taking the pain of figuring out what to monitor and building your own dashboards for weeks out of the monitoring.

https://kamon.io/apm/

Each of these tools can help you with micro service workload and work well. I will try to go through some good, bad and ugly of each.

Datadog has an easy setup and time to get something tangible out of it. The cost model is by host so this is something to take into consideration how it will affect your use case. Also as a large organization at some point you will probably want control over some/all of your telemetry data to run your own ML or AI processes. With Datadog you this can be difficult as you will need to create processes outside of its closed eco system to get Raw metrics.

Prometheus is a great tool. It also has a fairly straight forward setup especially with Kubernetes. If you are running your micro services in k8s then this is going to get used one way or another; it is a first class citizen there with heavy utilization of K8s API. I also like the fact that Kubernetes architecture is easy to understand and that it utilizes Grafana for the visualization engine. Prometheus at scale can be done but it is a pain. Especially with a distributed infrastructure across multiple workloads.

Influxdb (TICK stack in v1) is known for its scalability and flexibility as a time series database. Telegraf is the main input/data-forwarder of the architecture and is completely decoupled from the database as are the other 3 components of the stack. Influx has made it very easy to just use one component on its own. I have worked on stacks that just used telegraf for ingestion into Kinesis or another data stream. I have also worked on stacks that used Influx database but used a different ETL process for analyzing the data in realtime instead of using their v1 architectures Kapacitor query engine. Influx database is a great performing time series database that in version 2 runs within kubernetes and utilizes Flux as the query language. Flux is a nice query language that is fairly easy to learn and has a lot of flexibility. As a last positive note Telegraf is written in Go so that would fit well with your current team.

The difficulties of Influx are that it is hard to get something really tangible out of it. Initial time to see something is fast but all the other work involved is a lot. You also have to understand the architecture well. The management of Influx can be cumbersome but it can scale up better than the other two when Datadogs cost is taken into consideration. They have a lot of API hooks in their V1 enterprise edition to wire and configure it. They do offer a mange service to offload this cost until later.

My overall choice here is probably to go with some of the influx as you can rip and/or add components as needed into the flow. Eventually you will probably want to run an ML process within there (can be done within Kapacitor but of course can also use your cloud provider here too) and this gives you the flexibility to do it anywhere. I would still go through prometheus because you will most likely use it also, but it does have forwarders to Influxdb so still fits.

We're running Prometheus/Alertmanager/Grafana across our whole company for any monitoring and metrics requirement, from the infrastructure layer all the way up to Springboot endpoint services, the prometheus exporter / scraping approach works pretty well for us. It's really easy to setup and more importantly; to maintain it without much effort, all the Prometheus configs get automatically created through Terraform outputs and Ansible jobs. Combine it with Grafana and you're smiling.

We're moving towards Prometheus from Datadog at this moment. Main driving force is TOC at the moment.

Datadog is great until it becomes too expensive.

I worked with Datadog at least one year and my position is that commercial tools like Datadog are the best option to consolidate and analyze your metrics. Obviously, if you can't pay the tool, the best free options are the mix of Prometheus with their Alert Manager and Grafana to visualize (that are complementary not substitutable). But I think that no use a good tool it's finally more expensive that use a not really good implementation of free tools and you will pay also to maintain its.

this is quite affordable and provides what you seem to be looking for. you can see a whole thing about the APM space here https://www.apmexperts.com/observability/ranking-the-observability-offerings/