Apollo GraphQL – some pointers


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I’ve designed a variety of GraphQL schemas and developed microservice backends. But not done much with configuring the Apollo implementation of a GraphQL server until recently. This may reflect the fact my understanding of JavaScript doesn’t extend into the world of Node.JS as much as I’d like (the problem with being a multi-language developer is you’re likely to find your way around many languages but never be a master of one). Anyway, the following content is about the implementation within a GraphQL server part of a solution. It may be these pointers are just for my benefit you might find them helpful as well.

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To make it easy to reference the code, we’ve added entries (n) into the code, where n is a number. This is not part of the code. But there to make the different lines referenceable. Where code should go but is not relevant to the point being made I’ve added ellipsis ()

Dynamic loading and server configuration

import { ApolloServer } from 'apollo-server';
import { loadFilesSync } from '@graphql-tools/load-files';
import { resolvers } from './resolvers.js';   (1)
import ProviderInternalAPI from './ProviderInternalAPI.js'; (1)
import EventsInternalAPI from './EventsInternalAPI.js';  (1)
const server = new ApolloServer({
  debug : true,    (2)
  typeDefs: loadFilesSync('./schema.graphql'),   (3)
  dataSources: () => {
    return {
      eventsInternalAPI: new EventsInternalAPI(),    (4)
      providerInternalAPI: new ProviderInternalAPI() (4)

There is the potential to dynamically load the resolvers rather than importing each JavaScript file as we see on lines (1). The mechanics to do this is documented here. It would be cool if an opinionated implementation was provided. As shown by (3) we can take a independent schema file being loaded. The Apollo example approach for this didn’t seem to work for us, although both approaches make use of graphql-tools in a synchronous manner.

We can switch on debugging (2) for the GraphQL server, although the level of information published doesn’t appear to be significant. Ideally this setting is changed for production.

Defining the resolvers

The prefix for each resolver (1) must correlate to the name in the schema of the mutator or query (not the type as you would expect with Java). Often we don’t need all the parameters for the resolver. The documentation describes replacing each unused parameter with one or more underscores (i.e _, __ ). The underscore denoting the field not in use. However we can satisfy the indication of not being used, but keep the meaning of each position by using the underscore then a name (i.e. _parent, _args ) as shown in (2).

By taking the response into a variable (3) we can optionally log it. Trying to return using invocation line would result in the handler object rather than the payload itself. By taking the result into a variable we can log the content if desired and return the content.

The use of the backward quote is a node feature. It allows us to incorporate variables into a string by referencing it within ${} (4).

We need to supply the GraphQL server with instances with a layer of code that will interact with the resolvers. We can instantiate the instances in the declaration. The naming of the object is important (4) to the resolver.js (declarations).

import { useLogger } from "@graphql-yoga/node";
latestEvent (1): async (_parent, _args, { dataSources }, _info) (2)   => {
      if (log) { console.log("resolvers - get latest event"); }
      let responseValue = await dataSources.eventsInternalAPI.getLatestEvent(); (3)
      if (log) { console.log(`(4)  Resolver response for latest event:\n ${responseValue}`); }
      return responseValue;

Resolver declarations

 Query: {  ...
Mutation: {...
  Event: {  (1)
    providers: (event, args, { dataSources }, info) => {
      if (log) { console.log(`going to locate ${event.sources}`) }
      let responseValue = await (2) dataSources.providerInternalAPI.getProviders(event.sources);
      return responseValue;

To handle the use of resolvers within a larger resolver we need to declare the resolution outside of the Query and Mutator blocks (but inside the whole declaration block)(1). The name provided needs to match the parent entity that the query resolver contributes to.

To then provide values from the outer resolution we need to prover to the chained resolution use the naming as represented in the GraphQL schema as shown by (2). The GraphQL engine will resolve the mapping values.

Web resolver URL

  // GET
  async getProvider(code) {
    console.log("getProvider (%s) directing to %s",code,this.baseURL);
    return this.get(`provider?code=${code} (1)`);

The URL parameters need to be appended to the base URL path for the parent class to use in the invocation as shown by (1). The Apollo examples showed a setter option but we didn’t see the URI being addressed properly. This approach produces the relevant requirement.

K8s dashboard capability without needing to deploy K8s dashboard


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Let’s be honest we’re not all command line warriors when it comes to Kubernetes. I can get around Kubectl but the time it takes to key in a CLI command you can get the same information in a couple of clicks of the UI. For me, Kubectl is for automating my tasks, for example pushing a local build into a image repository, initiating a refresh deployment and ensuring old container instances are flushed out.

Lens view
K8s Dashboard

The only problem is that the K8s dashboard requires a lot of config work to secure its deployment, and do you want to be deploying such tools in a production environment? A colleague suggested I look at Lens. A tool that offers both Personal (free) and Team licensed versions and both versions deploy to Windows, Linux, and Mac natively so installation doesn’t require any messing around.

I have to say I have been very impressed with Lens. Everything useful about the K8s dashboard is here, but without needing to deploy anything to your cluster as lens runs as a local thick app. Just like the K8s dashboard you need the privileges to talk to the K8s APIs. But the Visualization is all local and the way the data is retrieved means the UI is very reactive.

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Lens supports extensions, although to date I’ve not tried any of the extensions personally – you can see a list of extensions here. I will be trying out a couple Of extensions in due course. For example:

Network Policy Viewer
Certificate Info (via K8s secrets)

Lens goes further by the fact you can connect to multiple clusters from a single viewer instance. So no need for multiple deployments of the dashboard or creating an additional management cluster.

I only have one minor grumble today with the implementation. When using a console facility to access a container it is not possible to paste into the console any text/script or copy out any of the log contents. The latter can make generating things like JIRA tickets a bit annoying. So far I’ve worked around it by creating screenshots.

Useful Resources

Securing credentials in Fluentd configurations


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When configuring Fluentd we often need to provide credentials to access event sources, targets, and associated services such as notification tools like Slack and PagerDuty. The challenge is that we don’t want the credentials to be in clear text in the Fluentd configuration.

Using Env Vars

In the Logging In Action with Fluentd book, we illustrated how we can take the sensitive values from environment variables so the values don’t show up in the configuration file. But, we’ve seen regularly the question of how secure is this, can’t the environment variable be seen by everyone on that machine?

The answer to this question comes down to having a deeper understanding of how environment variables work. There is a really good explanation here. The long and short of it is that environment variables can only be seen by the process that creates the variable and any child process will receive a copy of the parent’s variables.

This means that if we create the variable in a shell, only that shell and any processes launched by that shell can see the environment variable. So as long as we don’t set variables up as part of a system-level configuration then we already have a level of security. So we could wrap the start of Fluentd with a script that sets the environment variables needed. Then everything launches that script.

An even better way?

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Kubernetes Deployment – pulling from OCI Registry (OCIR)


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The following isn’t unique to OCIR, as it will hold true for any K8s Deployment YAML configuration that works with an Open Container Initiative compliant registry. To define the containers part of the YAML file we need to provide an attribute that can be used to confirm the legitimacy of the request. To do this we need to supply a token. However, we don’t want this token to be visible in plain sight in our YAML. The solution to this is to set up a secret within Kubernetes.

In the following YAML extract, we can see the secret is named.

kind: Deployment
  name: graph-svr-deploy
    app: arch-oke-graphql
  replicas: 1
      app: arch-oke-graphql
      name: graph-svr-deploy
        app: arch-oke-graphql
      - name: graphql-svr
        image: iad.ocir.io/ociobenablement/graphql-svr:latest 
        - containerPort: 4000    
          name: graph-svr-web
      - name: ocirsecret     

This does mean we need to create the secret. As this is a one-off task the easiest step is to create the secret by hand. To do that we use the command:

@kubectl create secret docker-registry ocirsecret --docker-server=iad.ocir.io --docker-username=ociobenablement/identitycloudservice/philip.wilkins@oracle.com --docker-password='xxxxxxxx' --docker-email=philip.wilkins@oracle.com

This naturally leads to the next question where do we get the secret?

This step is straightforward. Navigating using the user icon top right (highlighted in the screenshot below), select the User Settings option to get to the screen shown below. Then use the right-hand menu option highlight (Auth Tokens). This displays a section of the UI showing your current auth tokens and provides a button that will popup a window to guide you through creating a new auth token.

Related Posts

Image building across machine architectures for Oracle Container Registry (OCIR)


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In a previous blog (here) I wrote about the structure and naming of assets to be applied to OCIR. What I didn’t address is the interesting challenge of what if my development machine has a different architecture to my target environment. For example, as a developer, I have a nice shiny Mac Book Pro with the M1 chipset which uses an ARM architecture. However, my target cloud environment has been built and runs with an AMD64 chipset? As we’re creating binary images it does raise some interesting questions.

As we’re creating our containers with Docker, this addresses how to solve the problem with Docker. Other OCI Compliant containers will address the problem differently.


Buildx is a development feature in Docker which makes use of a cross-platform build capability. When using buildx we can specify one or more build platform types. These are specified using the –platform parameter. In the code below we use it to define the Linux AMD64 architecture mentioned (linux/amd64). But we can make the parameter a comma-separated list targeting different platform types. When that is done, multiple images will be built. By default, the build will happen in sequence, but it is possible to switch on additional process threads for the Docker build process to get the build process running concurrently.

Unlike the following example (which is only intended for one platform, if you are building for multiple platforms then it would be recommended that the name include the platform type the image will work for. For production builds we would promote that idea regardless, just as we see with installer and package manager-related artifacts.


docker login -u ociobenablement/identitycloudservice/philip.wilkins@oracle.com -p XXXXXXXXXXXXXXX iad.ocir.io
docker buildx build --platform linux/amd64 --push -t iad.ocir.io/ociobenablement/event-data-svc:latest
docker logout iad.ocir.io/ociobenablement/
kubectl apply -f ./deployment.yaml
kubectl apply -f ./event-data-svc.yaml

If you compare this version of the code to the previous blog (here) there are some additional differences. Now I’ve switched to setting the target tag as part of the build. As we’re not interested in hanging onto any images built we’ve included the target repository in the build statement. Immediately push it to OCIR, after all the images won’t work on our machine.

Useful Resources

Container Registry – pushing and storing containers


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A container registry is as essential as a Kubernetes service as you want to manage the deployable resources. That registry could be the public Docker repository or something else. In most people’s cases, the registry needs to be private as you don’t want to expose your product assets to potential external tampering. As a result, we need a service such as Oracle’s container registry OCIR.

The re of this blog is going to walk through how to push a container you’ve built into OCIR and a gotcha that can trip up users if you make assumptions about how the registry works.

Build container

Let’s assume you’re building your microservices locally or retrieving vetting 3rd party services for use. In both cases, you want to manually push your assets into OCIR manually rather than have an automated build pipeline do it for you.

To make it easier to see what is happening, we can exploit some code from Oracle’s Github repo (such as this piece being developed) or you could use the classic hello world container (https://github.com/whotutorials/docker-busybox-hello-world/blob/master/Dockerfile). For the rest of the post, we’ll assume it is the code developed for the Oracle Architecture Center-provided code.

docker build -t event-data-svc .

This creates a container locally, and we can see the container listed using the command:

docker images

Setup of OCIR

We need an OCIR to target so the easiest thing is to manually create an OCIR instance in one of the regions, for the sake of this illustration we’ll use Ashburn (short code is IAD). To help with the visibility we can put the registry in a separate compartment as a child of the root. Let’s assume we’re going to call the registry GraphQL. So before creating your OCIR set up the compartment as necessary.

fragment of the compartment hierarchy

In the screenshot, you can see I’ve created a registry, which is very quick and easy in the UI (in the menu it’s in the Developer Services section).

The Oracle meu to navigate to the OCIR service
the UI to create a OCIR

Finally, we click on the button to create the specific OCIR.


Having created the image, and with a repo ready we can start the steps of pushing the container to OCIR.

The next step is to tag the created image. This has to be done carefully as the tag needs to reflect where the image is going using the formula <region name>/<tenancy name/<registry name>:<version>. All the registries will be addressed by <region short code>.ocir.io In our case, it would be iad.ocir.io.

docker tag graph-svr:latest iad.ocir.io/ociobenablement/graphql-svr:v0.1-dev

As you may have realized the tag being applied effectively tells OCI which instance of OCIR to place the container in. Getting this wrong can be the core of the gotcha previously mentioned and we’ll elaborate upon it shortly.

To sign in you’ll need an auth token as that is passed as the password. For simplicity, I’ve passed the token in the docker command, which Docker will warn you of as being insecure, and suggest it is passed in as part of a prompt. Note my token will have been changed by the time this is published. The username is built on the structure of <cloud tenancy name>/identitycloudservice/<username>. The identitycloudservice piece only needs to be included for your authentication is managed through IDCS, as is the case here. The final bit is the URI for the appropriate regional OCIR address, as we’ve used previously.

docker login -u ociobenablement/identitycloudservice/philip.wilkins@oracle.com -p XXXXXXXXXXX  iad.ocir.io

With hopefully a successful authentication response we can push the container. It is worth noting that the Docker authenticated connection will timeout which is why we’ve put everything in place before connecting. The push command is very simple, it is the tag name assigned to the artifact including the version number.

docker push iad.ocir.io/ociobenablement/graphql/graph-svr:v0.1-dev
OCIR with several versions of a container

Avoiding the gotcha

When we deal with repositories from Git to SVN or Apache Archiva to Nexus we work with a repository that holds multiple different assets with multiple versions of those assets. as a result, when we identify an asset uniquely we would expect to name things based on server/location, repository, asset name, and version. However, here each repository is designed for one type of asset but multiple versions. In reality, a Docker repository works in the same manner (but the extended path impact is different).

This means it becomes easy to accidentally define a tag with an extra element. Depending upon your OCI tenancy privileges if you get the path wrong, OCI creates a new root compartment container repository with a name that is a composite of the name elements after the tenancy and puts your artifact in that repository, not the one you expected.

We can address this in several ways, first and probably the best option is to automate the process of loading assets into OCIR, once the process is correct, it will remain correct. Another is to adopt a principle of never holding repositories at the root of a tenancy, which means you can then explicitly remove the permissions to create repositories in that compartment (you’ll need to explicitly grant the permissions elsewhere in the compartment hierarchy because of policy inheritance. This will result in the process of pushing a container to fail because of privileges if the tag is wrong.

Visual representation of structure differences

Repository Structure
Registry Structure

Condensed to a simple script

These steps can be condensed to a simple platform neutral script as follows:

docker build -t event-data-svc .
docker tag event-data-svc:latest iad.ocir.io/ociobenablement/event-data-svc:latest

docker login -u ociobenablement/identitycloudservice/philip.wilkins@oracle.com -p XXXXX  iad.ocir.io
docker push iad.ocir.io/ociobenablement/event-data-svc:latest

This script would need modifying for each container being built, but you could easily make it parameterized or configuration drive.

A Note on Registry Standards

Oracle’s Container Registry has adopted the Open Registries standard for OCIR. Open Registries come under the Linux Foundation‘s governance. This standard has been adopted by all the major hyperscalers (Google, AWS, Azure, etc). All the technical spec information for the standard is published through GitHub rather than the main website.


Coding over Cocktails with Fluentd


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I’ve been fortunate enough to appear on a podcast with the excellent Coding Over Cocktails team from Toro Cloud. we got to talk about some of the ideas discussed in my Logging In Action book. You can check the podcast out via their website which includes all the episode details and links to all the platforms that host the podcast. There have been some great previous guests such as Luis Weir (my old boss), Chris Richardson of Microservices.io, Matthew Reinbold from Postman, Sam Newman to name just a few.

Visual Studio Code – Oracle Plugins


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Oracle’s product portfolio is significant, from databases (obviously) to GraalVM to a cloud platform capable of competing with GCP, AWS, and Azure. This means locating the Oracle-provided plugins, or community ones can get messy. Depending on your perspective Oracle Developer Plugins could relate to Java and GraalVM or Oracle Database.

As broad as the portfolio, is the Oracle details regarding the plugins. So the following two tables represent what we’ve identified as Oracle-provided tooling, and the second table of plugins we’ve used when working on Oracle-based solutions from the community.

Name / Plugin SearchDescription / Additional DetailsRelated resource links
search:Oracle Labs
This will return all the Oracle plugins related to GraalVM
There are several different extensions covering GrallVM
GraalVM Tools for Java
GraalVM Extension Pack for Java (the name here is a little miss leading as there is support for JavaScript, Python, Ruby, R)
GraalVM Tools for Micronaut
The extension packs also helps bring of SOA journey,
Oracle Developer Tools
(PL/SQL & Oracle Database)
Provider is Oracle Corporation
This extension enables editing and execution of SQL and PL/SQL for Oracle Database and Oracle Autonomous Databasehttps://www.oracle.com/

Oracle JET corelibrary of UI elements that form part of a web UI.Udemy training
Oracle NetSuiteSuiteCloud Extension for Visual Studio Code is part of the SuiteCloud Software Development Kit (SuiteCloud SDK), a set of tools to customize your NetSuite accounts.Netsuite dev blog
Oracle Provided Plugins

Name / Plugin SearchDescription / Additional DetailsRelated resource links
OCI Policy LanguageThis extension is a language highlighter for OCI Policies.
CPQ DevKitCPQKit™ is a website built to augment Oracle CPQ Cloud system’s functionalityhttps://www.cpqkit.com/
ApexIntelliSenseIntellisense for APEX
YAMLProvides comprehensive YAML Language support to Visual Studio Code, via the yaml-language-server, with built-in Kubernetes syntax support.
KubernetesThe extension for developers building applications to run in Kubernetes clusters
Language Support for JavaSupports Java 11 onwards
GitHub ActionsGithub actions is a means by which actions like commits to github trigger external infrastructure to perform actions such as creating application binaries.
Regexp Explainhelp to evaluate and develop regular expressions

Helping ‘mini me’ learn and practice Python coding


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My eldest son is studying computer science at school. As part of that course, like most educational settings they’re using Python to teach programming skills. Having sat with my son to help him get to grips with the coding the different ways of looping, implementing conditions, variable scopes and so on it has been interesting to see that school student level programming books take developers through very very simple steps with the rewards of success immediate but of limited value.

The challenge and concern, with this, is the step from this to delivering something meaningful, that continues to provide a sense of reward, while also something that is closer to real-world work.

This is where a small project I had comes into play. I have for many years been using an app called Orange CD catalog to record all the details of my music collection. The only problem is that it is a thick desktop app and the web solution called Racks and Tags hasn’t seen much development from what I can see for a long time and by current user experience looks archaic. As you may have guessed our pet project is to provide a web interface for the exported data from the Orange CD catalog. You can see the code in my GitHub repo here). I’ve carefully structured the code so the logic of processing the data (i.e. loops and conditions using data structures – using Python’s XMLTree library, which behaves a lot like lists – helping with basic learning). The web serving tier is implemented with Flask using simple annotations. This provides a nice opportunity to talk about the use of HTTP. The Jinja templates are also kept separate, so we don’t get bogged down with HTML, which can be a bit messy (IMHO).

Orange CD Catalogue

We’ll deploy the solution to our little Raspberry Pi, so it can be used anywhere in our network. Ultimately we could use it to stream the albums I’ve ripped to MP3. If my son wants/needs to learn a little bit about databases – then migrating the data into something like SQLLite becomes a simple development opportunity.

This does mean some prep work and including part of the solution, so something works very quickly. For me that’s fine, my Python web skills could benefit from some work and Jinja2 is new to me. But I could take the project embed suitable security and deploy it to my free Oracle cloud instance as a container into K8s. Those bits I won’t be sharing (minimize the risk of someone wanting to test how well I patch code etc).

Feel free to take the code and use it for yourself, extend, etc. But you don’t have to use my idea. The important thing is the idea is going to interest your child. But keep it simple. for example, if your child is a gamer, then perhaps you generate a simple data extract from the gaming servers to capture player performance, then your app does simple things like searching the content, sorting it, and providing a vanilla UI. The secret I think is each bit of the project is simple steps and not over well with heaps of code. Provide results quickly for example just search for an album by its title, and get the results into a webpage quickly.