Amazon CloudWatch vs. Splunk Infrastructure Monitoring

Cloud watch is great and essential if you decide to invest in AWS and have any need to monitor the health of all aspects of your VPC resources, or at the organizational level (multiple accounts). Another benefit of the service is constant upgrades at no additional costs; the software evolves to develop modules and interface improvements. For first-time users in AWS, this is going to take a bit to understand, so the learning curve to this metrics environment can seem overwhelming at first glance/use.

Incentivized

Splunk Infrastructure Monitoring is well suited for any complicated environment where you have apps and servers across multiple clouds and platforms and products. If you have a data centre where all your apps and servers are in one single network, you could probably get away with older solutions. But for any modern, complex, hybrid-cloud microservices environment, Splunk Infrastructure Monitoring is a must-have.

Incentivized

• It provides lot many out of the box dashboard to observe the health and usage of your cloud deployments. Few examples are CPU usage, Disk read/write, Network in/out etc.
• It is possible to stream CloudWatch log data to Amazon Elasticsearch to process them almost real time.
• If you have setup your code pipeline and wants to see the status, CloudWatch really helps. It can trigger lambda function when certain cloudWatch event happens and lambda can store the data to S3 or Athena which Quicksight can represent.

Incentivized

• SignalFX handles historical metric aggregation exceptionally well, providing a multifaceted approach to event detection based on anomalies.
• SignalFX's cost is incredibly flexible with their pricing model of DPM (data-point per minute) vs the traditional "per host" model that most monitoring SaaS use.
• SignalFX support is responsive and knowledgeable, very eager to help solve your immediate problems.
• SignalFX integrations is vast and constantly growing, making adoption easy even when multiple different open-source technologies are used in your stack.

Incentivized

• Memory metrics on EC2 are not available on CloudWatch. Depending on workloads if we need visibility on memory metrics we use Solarwinds Orion with the agent installed. For scalable workloads, this involves customization of images being used.
• Visualization out of the box. But this can easily be addressed with other solutions such as Grafana.
• By design, this is only used for AWS workloads so depending on your environment cannot be used as an all in one solution for your monitoring.

Incentivized

• Better integration with our clients (native mobile clients SDKs will be great).
• A way to easily tag filters and move them across metrics/formula.
• Alert system to easy false [alarm] and hard to configure.
• Be able to have group more dimensions (and have more values on each).

Incentivized

Good: Stable system with low error rate Easy to use for simple use cases Bad: UI is not very clear for complex usage Mobile view (when logged in from phone) is bad No library for .net

Incentivized

I find that learning the interface can take some time. We need a better show-and-tell on how the Teams pages, Dashboard Groups, Dashboards and charts delay. Advance SignalFlow is sometimes hard to build. Some better samples of advanced SignalFlow would be helpful. For example, Splunk SPL has a vast resource of examples.

Incentivized

Support is effective, and we were able to get any problems that we couldn't get solved through community discussion forums solved for us by the AWS support team. For example, we were assisted in one instance where we were not sure about the best metrics to use in order to optimize an auto-scaling group on EC2. The support team was able to look at our metrics and give a useful recommendation on which metrics to use.

Incentivized

I believe that CloudWatch is a better solution to use with AWS services and resources in terms of cost and ease of integration with AWS infrastructure services. But keep in mind that Elasticsearch is better at aggregating application-level metrics. We chose CloudWatch because of its capabilities to integrate and monitor AWS services in almost real-time.

Incentivized

They’re not for the same purpose but we’re using NewRelic and Honeycomb for monitoring purposes. NewRelic is used for HTTP client monitoring for system related throughput, error, database and external client monitoring. Honeycomb is used to monitor actual HTTP request/response values. Splunk [Infrastructure Monitoring] is used for real-time application related throughout and error monitoring.

Incentivized

• We were able to set up log streaming, retention, and simple downtime alerts within a few hours, having no prior experience with CloudWatch, freeing up our engineers to focus on more important business goals.
• CloudWatch log groups have made it relatively easy to detect and diagnose issues in production by allowing us to aggregate logs across servers, correlate failures, isolate misbehaving servers, etc. Thanks to CloudWatch, we are generally able to identify, understand and mitigate most production fires within 10-15 minutes.
• Choosing CloudWatch to manage log aggregation has saved us quite a bit of time and money over the past year. Generally, 3rd-party log aggregation solutions tend to get quite expensive unless you self-host, in which case you typically need to spend a fair amount of time setting up, maintaining, and monitoring these services.

Incentivized

• Reduced downtime.
• Caused us to get a lot of spam when we redeployed apps and old instances stopped sending metrics. Muting alerts solves this, but people often forget to do it or do it incorrectly.
• Helped us find historical info about instances/apps.

Incentivized