Amazon CloudWatch vs. Data Center Real-User Monitoring (DCRUM), discontinued

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

Dynatrace Network Application Monitoring (NAM), formerly DCRUM, has improved greatly compared to when it was DCRUM; however, it still needs a lot of improvement in end-to-end flow capture with regards to network monitoring. Its alerting and integration capabilities are very good and easy to use. But it still needs a lot of tweaking in usability.

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

• Dynatrace DCRUM can monitor legacy application protocols that are still used in a lot of organizations worldwide who still trust in those technologies.
• DCRUM monitors client-server architectures very well and can pinpoint issues along an infrastructure stack.
• Dynatrace DCRUM can analyze a wide spectre of protocols: Corba, DNS, DB2, Exchange, TCP, HTTP, IBM MQ, Citrix, ICMP, Informix, Tuxedo, SMB, LDAP, MSRPC, MySQL, NetFlow, Net8, Oracle Forms, RMI, SAP GUI, SAP HANA, SAP RFC, SMB, SOAP, XML.

• 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

• Major upgrades process is sometimes unpredictable.
• The use of SQL Server should be evaluated for something else.
• Easier SSL key handling.

Best of breed.

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

The only thing missing for a 10, would be if they texted or called you back.

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

Nagios can't trace real user transactions from a front-end tier through a backend-tier,;with Nagios you only can monitor server availability and hardware issues. Riverbed is commonly used to determine networking issues without considering real user transactions impact on an application stack.

• 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

• Dynatrace Network Application Monitoring (NAM), formerly DCRUM, helped us get a lot of info on an ongoing issue.
• It helped us figure out network bottlenecks in our environment.
• It is a very costly tool and a lot of other cheaper tools give same kind of info.

Incentivized