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AWS CloudTrail vs Logback: What are the differences?
Developers describe AWS CloudTrail as "Record AWS API calls for your account and have log files delivered to you". With CloudTrail, you can get a history of AWS API calls for your account, including API calls made via the AWS Management Console, AWS SDKs, command line tools, and higher-level AWS services (such as AWS CloudFormation). The AWS API call history produced by CloudTrail enables security analysis, resource change tracking, and compliance auditing. The recorded information includes the identity of the API caller, the time of the API call, the source IP address of the API caller, the request parameters, and the response elements returned by the AWS service. On the other hand, Logback is detailed as "A logging framework for Java applications". It is intended as a successor to the popular log4j project. It is divided into three modules, logback-core, logback-classic and logback-access. The logback-core module lays the groundwork for the other two modules, logback-classic natively implements the SLF4J API so that you can readily switch back and forth between logback and other logging frameworks and logback-access module integrates with Servlet containers, such as Tomcat and Jetty, to provide HTTP-access log functionality.
AWS CloudTrail and Logback belong to "Log Management" category of the tech stack.
Netflix, Slack, and Seat Pagine Gialle are some of the popular companies that use AWS CloudTrail, whereas Logback is used by Montoux, movix, and immmr. AWS CloudTrail has a broader approval, being mentioned in 50 company stacks & 59 developers stacks; compared to Logback, which is listed in 4 company stacks and 9 developer stacks.
We would like to detect unusual config changes that can potentially cause production outage.
Such as, SecurityGroup new allow/deny rule, AuthZ policy change, Secret key/certificate rotation, IP subnet add/drop. The problem is the source of all of these activities is different, i.e., AWS IAM, Amazon EC2, internal prod services, envoy sidecar, etc.
Which of the technology would be best suitable to detect only IMP events (not all activity) from various sources all workload running on AWS and also Splunk Cloud?
For continuous monitoring and detecting unusual configuration changes, I would suggest you look into AWS Config.
AWS Config enables you to assess, audit, and evaluate the configurations of your AWS resources. Config continuously monitors and records your AWS resource configurations and allows you to automate the evaluation of recorded configurations against desired configurations. Here is a list of supported AWS resources types and resource relationships with AWS Config https://docs.aws.amazon.com/config/latest/developerguide/resource-config-reference.html
Also as of Nov, 2019 - AWS Config launches support for third-party resources. You can now publish the configuration of third-party resources, such as GitHub repositories, Microsoft Active Directory resources, or any on-premises server into AWS Config using the new API. Here is more detail: https://docs.aws.amazon.com/config/latest/developerguide/customresources.html
If you have multiple AWS Account in your organization and want to detect changes there: https://docs.aws.amazon.com/config/latest/developerguide/aggregate-data.html
Lastly, if you already use Splunk Cloud in your enterprise and are looking for a consolidated view then, AWS Config is supported by Splunk Cloud as per their documentation too. https://aws.amazon.com/marketplace/pp/Splunk-Inc-Splunk-Cloud/B06XK299KV https://aws.amazon.com/marketplace/pp/Splunk-Inc-Splunk-Cloud/B06XK299KV
While it won't detect events as they happen a good stop gap would be to define your infrastructure config using terraform. You can then periodically run the terraform config against your environment and alert if there are any changes.
Consider using a combination of Netflix Security Monkey and AWS Guard Duty.
You can achieve automated detection and alerting, as well as automated recovery based on policies with these tools.
For instance, you could detect SecurityGroup rule changes that allow unrestricted egress from EC2 instances and then revert those changes automatically.
It's unclear from your post whether you want to detect events within the Splunk Cloud infrastructure or if you want to detect events indicated in data going to Splunk using the Splunk capabilities. If the latter, then Splunk has extremely rich capabilities in their query language and integrated alerting functions. With Splunk you can also run arbitrary Python scripts in response to certain events, so what you can't analyze and alert on with native functionality or plugins, you could write code to achieve.
Well there are clear advantages of using either tools, it all boils down to what exactly are you trying to achieve with this i.e do you want to proactive monitoring or do you want debug an incident/issue. Splunk definitely is superior in terms of proactively monitoring your logs for unusal events, but getting the cloudtrail logs across to splunk would require some not so straight forward setup (Splunk has a blueprint for this setup which uses AWS kinesis/Firehose). Cloudtrail on the other had is available out of the box from AWS, the setup is quite simple and straight forward. But analysing the log could require you setup Glue crawlers and you might have to use AWS Athena to run SQL Like query.
In my personal experience the cost/effort involved in setting up splunk is not worth it for smaller workloads, whereas the AWS Cloudtrail/Glue/Athena would be less expensive setup(comparatively).
Alternatively you could look at something like sumologic, which has better integration with cloudtrail as opposed to splunk. Hope that helps.
I'd recommend using CloudTrail, it helped me a lot. But depending on your situation I'd recommed building a custom solution(like aws amazon-ssm-agent) which on configuration change makes an API call and logs them in grafana or kibana.
Pros of AWS CloudTrail
- Very easy setup7
- Good integrations with 3rd party tools3
- Very powerful2
- Backup to S32