Some Google Cloud Platform services:

-Compute Engine: VM instances
-Cloud Storage: Secure scalable object storage
-BigQuery: Data warehouse
-Cloud Functions: pay-as-you-go functions as a service #serverless
-AppEngine: deploy apps quickly using popular languages without managing underlying infrastructure
-Cloud Run: Deploy your container to production
-Anthos: Enterprise-grade container orchestration and management
-Apigee: API Management Platform
-KNative: Serverless Platform
-Secret Manager: Store sensitive data

All services:

Why GCP:
-Google Compute Engine instances are charged in one-second increments with a one-minute minimum
-Google Cloud big data analytics solutions are serverless, removing the complexity of building and maintaining a data analytics system, so you can accelerate your time-to-insight.
-Google Cloud data centers run on half the energy of a typical data center, and run on 100% renewable energy where available


Redis is an in-memory database that persists on disk. The data model is key-value however many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes, Streams, HyperLogLogs, Bitmaps. (Even RedisJSON is a Redis module that provides native JSON capabilities)

I will use Ubuntu Desktop 20.04.02 LTS for this article.

Step 1: Install Redis Server

sudo apt install redis-server

Step 2: Start Redis Server and check its status

redis-cli ping

EC2: these are virtual machines you can leverage
- Instance types: check out for details
- Costs: spot instance (it can be taken by another bid) < reserved instance (planned to use) < on-demand (when needed)

- Unlimited object storage, versioning, encryption with different methods, you can even host single landing pages and use CORS
- Create your custom security policies: policy generator

EBS: this is block storage
- io2/io1 (high performance high cost, nosql dbs etc.)
- gp3/gp2 (medium performance reasonable cost)

Elastic Load Balancing: Assists you to session stickiness, handle auto scaled traffic to right instance


Docker is a containerization technology and Docker Swarm is a container orchestration tool.

I will use Ubuntu Desktop 20.04.02 LTS for this article.

Step 1: Get sample containerizated node.js web app

git clone

Step 2: Build the app

sudo docker image build -t myfirstcontainer .

Step 3: Configure Docker Swarm

sudo docker swarm init

Tempo for Jira is a paid add-on to gather timelog data from team members to analyze how much time is spent on relevant tasks. There are also paid Tempo Reporting add-ons to generate custom reports however it is quite easy to leverage Google Sheets and its query capabilities similar to SQL queries to generate the reports you require.

Google Sheets Sample Data:

Google Sheets Sample query:

=QUERY(A2:B7,"select sum(A) where B='First Week'")

Moskova metrosu ilk başta çok karışık gelse de aslında alışınca kolay, tek kafanızı karıştıracak şey kiril alfabesi olacaktır. Onu da aşmak kolay, kaldığınız yerden veya herhangi bir turist mekanından metro haritası nı alın ve ingilizce halleri ile orijinal hallerini eşleştirin. Bir yerden sonra zaten insan benzetebiliyor, sonuçta harflerin çoğunluğunun temeli alfanumerik.

5” nolu hat ring (daire şeklinde), yani diğer hatlara aktarma yapılabilmesini kolaylaştırıyor. Olur da yanlış hatla bir yere giderseniz diğer hatlara geçmek için bu ara hattı ve duraklarını kullanabilirsiniz.

İçi boş yuvarlaklar aktarma yapılabilen istasyon durakları, o durakta indikten sonra levhalar aracılığı ile diğer hatta gidebiliyorsunuz. Bazı duraklarda…

Grafana is an open source observability software which could be downloaded from here and if you prefer to play online without installing check out here.

I will use Ubuntu Desktop 20.04.02 LTS for this article.

Installing Grafana with docker is super easy, first you need docker to be installed on your Ubuntu OS which can be achieved via below command:

sudo snap install docker

then you can download and run the Grafana docker image:

sudo docker run -d -p 3000:3000 grafana/grafana

or if you do not prefer docker, you can install natively via the commands below:

sudo apt-get install -y…

Previously I had shared an article about installing minikube and deploying apps. You can also leverage Microk8s package of Ubuntu which is easy to work with.

I wanted to share a serverless approach you can leverage on top of Kubernetes which is KNative at this article.


Protocol: TCP
Host IP:
Host Port: 22
Guest IP:
Guest Port: 22
  • We want to copy/paste commands from host machine to virtual machine so we will…

I had played a little bit with minikube on Mac to understand how kubernetes work from installation to deployment at 2019. Sharing my notes as steps which might assist.

Step 1: Minikube Installation On Mac

Minikube is an all-in-one kubernetes that you can install at your local machine to play and learn about Kubernetes. Minikube Documentation


Before installing minikube itself, you should install kubectl command line interface (CLI), I had installed minikube to macos via Home Brew:

brew install kubectl
after successful install you can start check kubectl below command:
kubectl version

Sample output

kubectl version
Client Version: version.Info{Major:"1", Minor:"14", GitVersion:"v1.14.7", GitCommit:"8fca2ec50a6133511b771a11559e24191b1aa2b4", GitTreeState:"clean", BuildDate:"2019-09-18T14:47:22Z", GoVersion:"go1.12.9", …

When you are handling customer interactions throughout Jira Service Desk, you most probably will need to see overall report of what is going on. In order to achieve these kind of requirements there are couple gadgets you can leverage.

Use case 1: I want to see percentage distribution of tasks’ status/issue type/assignee/priority etc.


Step 1: Create your relevant filter at Filters → Advanced issue search→ Save As

Your data needs come from a filter which you can create one on

You can save the filter something like “All Waiting”

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