Forgerock UnSummit Bristol 2017 Notes

10:00 Kickoff

Agenda of the day
Finalised agenda of the day @ Forgerock UnSummit Bristol 2017

Forgerock on Docker

Start off with base docker image containing OpenAM. This docker image has a folder for config which can be volume mounted to allow loading custom config. During runtime, it detects the config and runs it against amster (ssoadm replacement). Continue reading

AppDynamics Power User Training Notes – Day Three

Dashboards. Useful for displaying and sharing information across teams or departments. Allows integrating other tools via iFrame widget. Dashboards can also be embedded into other services or even web pages.

A dashboard can also be converted into a report. One can also schedule periodic emailing of reports to a recipient list. This might be useful to create a “weekly/monthly digest” of data relating to an environment.

Policy triggers define events that trigger actions. When the criteria in a policy is met, a corresponding trigger is activated. This can be used to control behaviour such as increaing thread pool size as load increases etc. The trigger must be associated with a health rule violation. For example, if a health rule specifies “calls higher than normal” then a policy can be created based on this heath rule. The trigger gets executed when violation of the specified health rule occurs. Triggers can span different stages of health rule violations, for example, start and/or end. More than one health rule violation event can be specified. Continue reading

AppDynamics Power User Training Notes – Day Two

Health rules are conditions that if fulfilled relate to good health for a particular node. The conditions can be based on load (calls/min), response times (x ms average) or error rate. AppDynamics provides 7 health rules out of the box. When one or many health rules are violated, an alert is issued. Depending on the integrations configured, this alert can be an email or SMS.

Health rule can be based on transaction performance or node health. In case of transaction performance, it can target specific transactions or all transactions in a tier. However, in case of node heath, this can target specific node or nodes in a tier or nodes by type.

The data that health rule uses can also be configured. This can be a time period that it should use. This can be in free form numeric minutes. One can also specify wait time after a violation, i.e. how long should it wait to reassess health rule after it has been violated. This should be long enough so that it has enough new data to positively reassess the condition. Continue reading

AppDynamics Power User Training Notes – Day One

Node is mapped to individual JVM or CLR application in environment. If an environment has multiple JVMs running then each maps to a node.

Tier is a logical piece of application. For example a piece of functionality. Each web server has node. A single tier can span multiple web servers and each of those web servers can contain multiple nodes.

Application traffic is organised into business transactions. Each transaction is a distinct user activity like Login or register etc. When a request comes in for the first time, it is tagged with a GUID and that GUID is tracked across the environment. Requests with similar patterns are grouped together. This group is then given a default name. This is default name is based on how the application is designed.

Since each business transaction works across nodes, each has its own flow map. Continue reading

Notes from AWS Developer Training (Day Three)

Creating Serverless Projects

In a server less environment, Amazon Lambda can be used in conjunction with Amazon API Gateway for HTTP interfacing, Amazon S3 for storage, Amazon ElastiCache for caching and DynamoDB/RDS for database storage. Checkout the Servless Application Framework at serverless.com for more info.

Securing data in AWS

Infrastructure should be treated as code, I.e. Version control systems. Automate security and increase testing frequency via CI/CD. Fail early and fast. Test at production scale. No need to keep the test servers alive. Spin up the entire production environment in test, deploy the code, run the tests and then tear down the environment. Continue reading