If you’re interested in using Docker on AWS Windows using a Windows image, turns out you’re out of luck:


Docker is not currently supported on Windows WorkSpaces:

Articles, notes and random thoughts on Software Development and Technology
If you’re interested in using Docker on AWS Windows using a Windows image, turns out you’re out of luck:


Docker is not currently supported on Windows WorkSpaces:
Trying to install some Python packages with pip inside a Docker container I ran into this issue:
# pip3 install pytest
Collecting pytest
Retrying (Retry(total=4, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError('<pip._vendor.urllib3.connection.VerifiedHTTPSConnection object at 0x7feb52c30630>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution',)': /simple/pytest/
At first I thought this something to do with network restrictions since I’m running this on a Linux AWS Workspace, but I have internet access enabled. Running the command on the Workspace itself works as expected, so this is something specific to the Docker container. Next I thought this might be something to do with the specific container image I was using, but after trying a few others I had the same error on any container.
Searching for the error “Failed to establish a new connection: [Errno -3] Temporary failure in name resolution” online I found this question and answer, and suggested to run the Docker container with the host networking option.
So instead of running bash in the container like this:
$ docker run -it tensorflow/tensorflow:1.12.0-py3 bash
Pass in the network=host option like this:
$ docker run --network=host -it tensorflow/tensorflow:1.12.0-py3 bash
# pip3 install pytest
Collecting pytest
Downloading https://files.pythonhosted.org/packages/b1/ee/53945d50284906adb1e613fabf2e1b8b25926e8676854bb25b93564c0ce7/pytest-6.1.2-py3-none-any.whl (272kB)
100% |################################| 276kB 9.4MB/s
Problem solved!
If you attempt to access an AWS Workspace running Linux via a browser, you’ll get his spinner for what seems like a couple of minutes:

Eventually it times out with this error:

Looking in the docs here this is this note:

Web access to Linux WorkSpaces is currently not supported. Would be nice if it gave you an error when to attempt to logon to tell you it’s not a supported option instead of just falling.
The Serverless.com cli gives 2 Lambda project type options for new projects – Node,js and Python:
% serverless Serverless: No project detected. Do you want to create a new one? Yes Serverless: What do you want to make? AWS Node.js AWS Python ❯ Other
If you select Other, it prompts you to create a project using a template:
Run “serverless create --help” to view available templates and create a new project from one of those templates.
The ‘create –help’ option tells you to run with the –template option and provides a long list of supported project types. Since I’m using Maven with Java, I’ll use the aws-java-maven option:
serverless create --template
Since I already had a Maven pom.xml in place as a starting point for my Lambdas in this test project, the serverless cli warns that it won’t overwrite the existing file. I’m not familiar with what additional dependencies the aws-maven-template will add, so I renamed my pom.xml and reran the ‘serverless create’ cli and generated a new pom.xml.
Looking in the new file, there’s a similar and expected use of the Maven Shade plugin to bundle a ‘fat jar’ and other dependencies for Log4J and the addition of Jackson for json parsing.
There’s also a couple of extra Classes generated too that I wasn’t expecting, but they match up with the example code in the serverless docs (article here), so there’s a ApiGatewayResponse class that I wasn’t familiar with (from building AWS Lambdas with Java by hand and not using the API Gateway Lambda Proxy feature).
As a test, I looked into creating a couple of Java Lambdas not using the generated Classes just to confirm that there’s nothing Serverless framework specific that needs to be used. As it turns out, the default usage of the APIGateway Lambda Proxy feature the Lambda runtime is is expecting to map a json payload into the handler parameters and similarly for the response payload. For testing I just wanted to pass a couple of String request params on a GET request. So for my first test I got the following exception:
An error occurred during JSON parsing: java.lang.RuntimeExceptionjava.lang.RuntimeException: An error occurred during JSON parsingCaused by: java.io.UncheckedIOException: com.fasterxml.jackson.databind.JsonMappingException: Can not deserialize instance of java.lang.String out of START_OBJECT token at [Source: lambdainternal.util.NativeMemoryAsInputStream@4cf777e8; line: 1, column: 78] (through reference chain: java.util.LinkedHashMap["headers"])Caused by: com.fasterxml.jackson.databind.JsonMappingException: Can not deserialize instance of java.lang.String out of START_OBJECT token at [Source: lambdainternal.util.NativeMemoryAsInputStream@4cf777e8; line: 1, column: 78] (through reference chain: java.util.LinkedHashMap["headers"]) at com.fasterxml.jackson.databind.JsonMappingException.from(JsonMappingException.java:148)
At this point I got distracted with a wide range of Java Lambda together with the API Gateway Lambda Proxy specific issues which I covered in a separate post here.
Long story short, the Serverless config for a Java Lambda enables the API Gateway Lambda Proxy feature by default, which means your Lambda impl needs to have a POJO class for it’s return type that matches exactly what API Gateway expects, so the Lambda to API Gateway Proxy integration can map the return value to the expected JSON structure. You can build this yourself to match what is described in the docs (link above) or just use the provided class generated by the aws-java-lambda template. The generated class ApiGatewayResponse is exactly what you need, so rather than reinventing the wheel I changed to use this generated class as the return value from my Java Lambda handler and now it works as expected.
My handler now looks like this:
public class MyHandler implements RequestHandler, ApiGatewayResponse> {
@Override public ApiGatewayResponse handleRequest(Map<String, Object> input,
Context context) {
}
}
Note that in order to receive parameters from incoming requests via API Gateway proxy, the first parameter needs to be a Map<String, Object>.
This is the first time I’ve used API Gateway Lambda Proxy with Java Lambdas. Previously the JavaLambdas I’ve built took advantage of API Gateway mapping any parameters to your Lambda automatically using Jackson to a POJO parameter on your Handler method, and even handing a POJO return type serializing that to a JSON response for you. I’ll come back and do some comparisons between these two approaches later.
To deploy your Java Lambda using serverless it’s the same as with Node.js Lambdas or any other supported runtime:
serverless deploy
To test calling your Java Lamdba function locally as if it’s deployed to AWS, use
serverless invoke local --function functionName
where functionName is what to defined your handler as in your serverless.yml.
By default the generated ApGatewayResponse class doesn’t have a toString() so you’ll see the response to your local test print something like:
com.serverless.ApiGatewayResponse@9301672
but you can add a toString() to help with testing locally (this is mentioned in the docs here).
The servless.com framework saves a lot of time in automating the deployment and configuration of your Lambdas and is well worth a look.