How to make current job more fulfilling

Are you losing interest in your current job? Do you feel perhaps changing it will bring more happiness? Before you go further with stronger steps, what if you re-evaluate your situation? Is it really the job you less like or something else within the job that needs adjustments? Let’s review some steps on how we can make our current job more meaningful:

  • Know why behind the job you’re in: Understand why you’re in this job. Is it your financial responsibility that’s bringing you to the work every day? Why did you choose this line of work? Does it relate to your interests?
  • Is there anything that is lacking in the current job? Evaluate reasons what can increase the engagement at work. What growth perspective you’d like to focus on? Is it more salary? Is it the increase in the impact to the people or business you support? Is it the technology/skills you use at work? Here’s a quick trick to evaluate. Would you prefer to continue doing the work you do, if:
    • You’re offered 2 times the current salary or
    • You’re offered a promotion or
    • You’re offered to increase your business impact or
    • You’re offered to work with more people or
    • You’re offered to switch to use different technology/skills
  • Evaluating it would help to increase the engagement. If we find out that we should move for a better option, we should plan for it. Sometimes, we find out that we’re already in a great environment. For example, a friend of mine was not engaged at work. After the analysis, he realized that given two times the salary, he’d continue working at the same place with the same set of people, supporting the same business. So, there was nothing wrong in his current job except a low pay situation. He decided to explore if he’s really paid low. The reality was that he’s reasonably paid. His comparison of low-pay was also somewhat unreasonable. Sometimes, it’s our comparison, judgement, and other such inner-enemies that cause us distress. Sometimes some people have a feeling that we’re not doing enough or we’re simply not happy where we are. After the realization, he’s now focusing on his current job with a desire to increase his impact. Another person in a similar situation found out that he can get a better salary outside. He planned to move to a better paying job.
  • What’s the minimum required from you at work: Make a list of minimum required expectations from you at work. How knowing the minimum required expectations help? Many times, we’re overwhelmed and lost with many demands at work. Sometimes, it becomes confusing to navigate the day at work successfully. Making a list of minimum required tasks provides us the clarity of expectations. For example, if someone is a software developer at work, they can write minimum required tasks as:
    • Prime tasks like driving projects A, B, and, C. Write down what’s the minimum required expectation for each project.
    • Supporting tasks: update on progress every week, month, and quarter. What does it means? How much times does it require every week?
    • Trainings: are there any mandatory trainings that you have to attend?
  • After making a list of minimum required tasks, plan your time at work to first address these tasks. In my experience, I noticed that many times, ambiguous situations and confusions take up a lot of time. Without the clarity of minimum required tasks, we maybe wasting time. After a certain time, we start being overwhelmed with many things undone.
  • Look at the bigger picture of your current job. Let’s look at three areas to evaluate it:
    • People: how are your work relationships with people? Do you feel connected with people at work? Can you make friends at work to share your life and listen to their life situations? Connecting with people at work can make the work more interesting. Also, knowing that you’re not alone in life’s common challenges can help to find mentor support. For example, a friend found that his colleague also has interest in writing. What if he and his colleague can find moments in the day to share their writing content?
    • Business: what business does your job supports? What’s the bigger picture of it? For example, are you in an IT development job? What social cause your company support? If it’s a public company, what is the sector of your company’s stock? How your work impacts the society? When we relate our work with a larger cause, it could help in bringing the engagement.
    • Technology/Skills: What skills do you need, to perform your current job? What are your areas of expertise? How valuable are those skills in the outside market? Is there any skill that other would like to learn from you? If you’re interested in mentoring others, would you like to mentor someone at work? Is there any particular skill you’d like to learn more at work?
  • Plan for periodic leaves. Sometimes, we feel that we have no choice other than going to the same work every week. Taking leaves helps us to reflect upon life. If it’s feasible, plan for a longer leave, like a week. If you’re free without any work tasks, what do you feel to do? For example, my one friend likes learning about technologies even when he’s out of the work. He’s naturally inclined towards technologies. By taking leaves, he realized that even if he doesn’t need a job for his financial needs, he’d like to write programs in his free time. He realized that it’s not the work type that he wants to change. Sometimes, he’s overwhelmed at work. So, the solution is to find out how can he prioritize his work so he can set the right expectations.
  • Plan for continuous evaluations: Plan for a periodic evaluation to assess where you’re. If you’re interested in something else, keep pivoting from the current situations. For example, after a decade of experience in a technical skills set, if you’re interested in moving to a new skills set, start planning for a steady move.

I’d love to know yours feedback on it. Thank you.

Common Design Patterns Overview

In this article, we’ll go through the overview of basic design patterns.

Circuit Breaker: This is a pattern that helps to manage calls from one service to another. There are three states of it:

  • Open: Calls from one service to another service are not allowed.
  • Closed: Calls from one service to another service are allowed.
  • Half-Open: A few calls from one service to another service are allowed but not all calls are allowed.

Two implementations for circuit breakers: Hystrix and Resilience4J.

Bulkhead: It allows to set maximum concurrent users that can connect to a service.

Backpressure: We will add details of it later.

Bloom filters: it is a data structure to search an element in a data set quickly with the level of certainty. Guava is a known Java API implementation of bloom filters.

HyperLogLog: it is a data structure that can provide the probabilistic calculation of the cardinality of a data set. Let’s say we want to understand how many unique visitors visited a mall. We can use HyperLogLog data structure to do it efficiently.

Gang of Four Design Patterns: It consists of three types of patterns: structural, creational, and behavioral, In total there are 23 of patterns.


Bloom filters:


Interview questions on leadership skills

Audience: anyone conducting/preparing for a technical leadership interview position.

What’s the best way to work with executives?

To work with executive, I prefer to follow the formal process per the company standards. Executive’s time is generally limited and they prefer a brief and to the point communication. Before reaching out to executives, it is important to understand if the topic worth the need of executive’s time. If it needs the time from executive, setting the expectation is important. I will determine if the topic to share with executives is to provide an information, or ask for any feedback or a decision. If it is about asking a decision, it’s helpful to prepare options. If a help is needed for an executive, it should be clear what kind of a help is needed. Executives prefer a clear communication and expectations. I will plan for it accordingly.

Is consensus always a good thing?

Consensus is not a good thing always. Depending on the situation, this strategy should be used. In my experience, there was a product that was working on a stable way but the company needed something completely innovative. To get such an environment, a leader challenged the existing environment. He did not have the consensus to proceed. But he did the right thing. In other situation, a consensus helped when I had to make a go/no-go decision on a success of failure of a User Acceptance Testing. Consensus helped as there were only few people in oppose and all such open issues could either be delayed or worked around.

What is the best way to work with customers and users?

The best way to work with customers or users is to understand their perspective and requirements. I believe the main goal of a product is to meet a customer’s or a user’s needs.

What kinds of people do you like to work with?

I like working with people who can collaborate well towards a common goal. This needs keeping individual approach secondary and thinking and planning for a common objective. This needs individuals to think beyond their individual achievements and focus on a teamwork. It is important to understand everyone’s perspective in the situations. The final decision must be that is needed for the success of the common goal.

What kind of people do you have a hard time working with?

I get hard time working with people who do not think for the success of the common goal. Instead, they may be driven from some other individual or team goals. To deal with such situation, I prefer to remind everyone about the common goal.

What would you do to get a team to stick to a schedule?

This depends on the type of the task. I will first provide a high level context of why we have a schedule and what do we want to achieve as a team within a schedule. Then, I will prepare a plan with everyone’s collaboration. Once everyone agrees with the plan and understand why we want to stick to the schedule, I suggest someone to schedule recurring meetings to check the progress status, blockers, and next steps. Ib the middle of the schedule, I prefer to remind everyone why this schedule is important , why we all agreed to it, and what are positive consequences of sticking to the schedule.

What’s the difference between leadership and management?

Leadership is about influencing, inspiring, and enabling others to make a positive impact. Management is about controlling group or entities to complete a goal on time.


As I learn more, I will update this page. Thank you !

How to learn 1-hour every weekday

In any career track, it is important to keep learning. For example, technologies are changing with a rapid speed. It’s important to keep learning if you are in a technology career. Everyone talks about learning continuously and everyone understands the importance of it. How to really keep yourself updated? I went through a very informative article about a 5-hour rule of learning every week. As per this rule, learning one hour every week day is required to stay up-to-date in your field. If we are convinced to follow the 5-hr rule, here are few ideas on how to make it happen:

  1. Accountability:

How to make yourself accountable for it to make it happen? These are few ideas:

  • If you like writing (as I do), what if you commit yourself to come up with one article of the week that you share with your audience what you learned this week? It could be a simple article about one single technical topic or anything you learned. Can you commit your audience to know by Friday evening or Saturday morning what you learned in the week? If you like writing, what if you start your auto-biography in that you write about each week’s learning?
  • If you like speaking, can you create an audio clip about what you learned in the week?
  • If you like painting, can you draw a picture about what you learned in the week?

Some other ideas for accountability: Imagine you are an IT consultant who has to fill-up a weekly timesheet that has a section of 1-hour learning every day. Imagine that the timesheet will be approved only if the 1-hr learning section is filled up.

2. Fix the learning hour for every weekday:

If we can set a fixed time in the day every week for the learning, it has more chances that we will not miss it. By chance, if you missed it, ensure to cover it up before sleeping. In the worst case, one cheat day in a week is ok. Here are some ideas on how to fix the hour for the learning:

  • Morning time: What if we get-up one hour earlier and use that hour for learning? It needs determination and assumption. Assume we had to get up one hour earlier. What if we start reaching work one hour earlier and use that hour for learning? Avoid the temptation of checking emails or other distractions.
  • Lunch time: What if we convert the lunch hour as a learning hour? We will not get a complete hour but 20 minutes quality time is a possibility. 
  • In between the work hours:  What if we block one hour every day at work for learning? The difficulty is to avoid the temptation of replacing it with an urgent meeting or task. One cheat day is ok. What if we go home one hour late?
  • Before sleeping: What if we plan to sleep one hour late?

3. Be realistic with your goal:

An example of an unrealistic goal would be to complete a 500-page book in a week. An example of a realistic goal would be to understand one topic of the book every day. Here is another key to plan. If you think we can finish three topics in the day, then, what if we reduce it to one third of the goal?

4. Temptation to skip it today:

There are high chances you may be tempted to skip it just today because today is a busy day. It will happen many times. Remember. Everyday is a fresh day for new opportunities.

Decide today the topic for tomorrow:

If we don’t know what the topic is for tomorrow, we have a high chance to skip it tomorrow. So, it’s critical to be specific about the learning goal for tomorrow. A better idea is to plan for a week in advance. If at the moment we feel like learning something else, we should note it. Delay the next topic to another hour, if we get it in the day. Consider it as a work meeting on the decided topic that has the deadline today.

5. Other difficulties:

  • We may face a difficulty of breaking the topic in small units. So, to challenge it, consider it as a project with a go-live date. Break the work down into a small unit of work that takes about 20 minutes to finish.
  • What if you are not in the mood to learn today? This task is not for today and it can not be dependent on the mood today. It is a task for the future that has to happen today. If you are upset or angry about a situation at work, consider this task as an activity to change this situation in the future. It is anyway a good idea to let the day go in a flow, write down such moments, and review those at the end of the day.
  • What if you had some emergency situations at work or at home? Use it as a cheat day or try to adjust other things on the plate.

I would like to know your views about 5-hr learning rule and your ideas about how to stick to this rule.

Databases basics

Who should read it: It is for you if you are looking for an overview of this topic for a project, to conduct/appear in an interview, or in general. As we learn more, we will update this article.

Why we need distributed databases: 

  • Difficult to store entire data set into a single database
  • Single point of failure
  • Slow in performance
  • If we make a big computer, it will be more expensive

For the distributed database architectures, we have a master database and can have multiple secondary databases. Single node databases are classic databases like PostgreSQL, MySQL, etc. Distributed databases are made of multiple nodes. These are fault tolerant. Database clusters means multiple database instances. In general, we have leader nodes and follower nodes. Leader node is in charge of returning the final data results. Followers receive the data. If the leader node fails, a follower node can become the leader node.

Types of distributed databases:

  • Big compute databases: Split data across multiple nodes. These are suitable for analytical workloads.
  • High availability databases: are extremely fault tolerant. Each node has a full copy of the data.

Some key points about distributed databases:

  • Imbalance node: the problem when a node has more data load. Moving the data between nodes is slow.
  • Asking data from hard disk is slow. Asking data from RAM is fast.
  • Leader node examines the query. Leader node distributes the jobs to different nodes.
  • Sharding: It is a model in that all database instances acts as the primary databases. We segment data into multiple instances. Problem is that if we have more load on one segmented database, it will cause problems. Also, if we have to join data with two databases, we will have network connections.

CAP theorem:

  • C stands for Consistency. If we write information, we want to get same data. That is the consistency. To maintain consistency, data in the primary and secondary databases should replicate asap.
  • A stands for Availability. If we have two databases, if one machine goes down, as a whole system, users should be able to read or write.
  • P stands for Partitions. Partition tells us that even if connections to two machines not working, we should still be able to read/write the data.
  • RBDMS databases provide strong consistency. NoSQL databases generally prioritize availability, partition tolerance, and provide eventual consistency.

As per CAP theorem, generally, databases can achieve up to two features out of three. For distributed databases, assume network failures will be inevitable. So, for distributed databases, we need to choose between C and A.

PACELC theorem:

As per CAPLEC theorem, if partition happens, choose Availability and Consistency. Else, choose Latency and Consistency.

Other theorems:

BASE: BASE stands for Basically Available Soft state Eventually Consistent. NoSQL is an example of a BASE.

  • Basically Available: The system is guaranteed to be available in event of failure.
  • Soft State: The state of the data could change without application interactions due to eventual consistency.
  • Eventual Consistency: The system will be eventually consistent after the application input. The data will be replicated to different nodes and will eventually reach a consistent state. But the consistency is not guaranteed at a transaction level.


Database index is a data structure that helps to retrieve data faster from a table. Indexes are like library catalog that helps to know the location of a book. For more about index, refer here.

Relational databases:

Relational databases store data in rows and columns. Some famous relational databases are MySQL, Oracle, and Postgres.

Advantages of relational databases:

  1. Well defined relationships and structured: data in relational databases is structured, with foreign and primary key constraints. It helps in organizing the data. Defined relationships and structure also helps in retrieving the data effectively.
  2. ACID (Atomicity, Consistency, Isolation, Durability): As relational databases support ACID properties, it’s helpful in ensuring the data changes for a transaction.

Disadvantages of relational databases:

  1. Rigidity due to structured data: As the data is well defined and structured, it’s not easy to store a new data set for that a structure is unknown. For example, to add a new column into a table, the table has to be changed, to support it.
  2. Difficult to scale: scaling means supporting more volume of data. For relational databases, scaling is difficult. For read-only operations, it’s easier to replicate the data. For write operations, a general approach is to add more capacity (vertical scaling) to the primary database server, which is costlier than replacing read-only databases.

NoSQL Databases:

There are multiple types of NoSQL databases like:

  • Key-Value storage type: Data is stored in key-value pairs in arrays. Some examples of such databases are Redis and Dynamo databases.
  • Document databases: In these databases, data is stored in the documents. A collection is a group of documents. Each document can have a different structure. An example of such a database is MongoDB.
  • Wide-column databases: In these databases, the number of columns can vary per row in the same table. We can consider it as a two dimensional key-value storage. Some examples of wide-column databases are Cassandra and HBase. For more, refer here.
  • Graph databases: These represent data in a form of a graph. Examples of such databases are Neo4J and Infinite graph.
  • Some NoSQL databases:
    • Couchbase: It is a NoSQL database that stores the data either in key/value pair or in JSON document format. In a traditional database model, we begin with a schema. We add tables and the columns in the tables.
    • MongoDB: MongoDB is an open source document database. It works on concept of collections and documents. A collection is a document which is equivalent to an RDBMS table. A document is a set of key-value pairs. It is a schema-less database. It is easy to scale. It is a good choice for a Big Data need.

Advantages of NoSQL databases:

  • Flexibility with unstructured data: As the data in NoSQL databases is unstructured, these databases provide more flexibility to store the data.
  • Horizontal scaling: Horizontal scaling means distributing data into multiple server instances. Data in NoSQL databases are distributed, by using sharding. These databases support horizontal scaling for both, read and write operations.

SQL versus NoSQL databases:

  • Storage: Data in SQL databases is stored in rows. NoSQL databases have different data storage models like key-value or graph
  • Schema: SQL databases have a fixed schema. noSQL databases can have different schemas.
  • Querying: SQL databases use Structural Query Language (SQL), to retrieve the data. NoSQL databases uses UnQL (Unstructured Query Language). NoSQL are focused as a collection of documents.
  • Scalability: Horizontal scaling in SQL databases is difficult as compared to NoSQL databases.
  • Reliability: Most SQL databases are reliable and ACID compliant. Whereas, NoSQL databases may compromise reliability and ACID compliance.
  • Language: SQL databases use transactional SQL. They support core ANSI/ISO language elements. Whereas, NoSQL databases are not limited to one particular language. For example, MongoDb uses Javascript based query language.

 How to choose between SQL and NoSQL databases:

  • Consider SQL databases when:
    • Data is structured and structure is not changed frequently.
    • Supporting transaction-oriented use cases.
    • No need to scale the database.
  • Consider NoSQL databases when:
    • Data is not structured and the structure can change frequently.
    • A flexibility of dynamic schema is needed.
    • We anticipate the scaling of the database in the future.
    • Level of data integrity is not needed.

Other databases terms:

  • Purpose built databases: There are many options like relational database, key-value database, document database, graph database, in-memory database, time series database, and ledger database. Depending on the situation, today’s application developers need to pick a right database for the use case, by analyzing pros and cons of the situation.

Partitioning and Sharding: it is the process of splitting the data into columns or features. Vertical partitioning splits the data into the same database by columns or features within the same tables. Horizontal partitioning splits the table data to multiple shards ( e.g. multiple database locations). In case of sharding, a table may have a customer ID 1 on one server and customer ID 2 on another server. In case of partitioning, other customer Ids 1 and 2 are on the same database servers and in the same table.

Distributed transaction types:

  • Two-phase commit (2PC): In case of 2 Phase commit, there is a coordinator that prepares multiple transactions. Then, the coordinator either commits or rolls back all transactions together. While preparing each transactions, the database table rows (that to be updated in DB) are locked using local transactions. This prevents any updates during the 2-phase transaction. We also need to plan for a time limit for each transaction so that the coordinator is waiting to commit or rollback within a defined time period.
  • 3 phase commit: First phase is that the coordinator asks if it’s ok to commit. Second phase is to pre-commit the transaction. Third step is to commit a transaction. I’m yet to learn more and add more notes about it.
  • Try-Confirm/Cancel (TC/C): In the first phase, the coordinator asks all databases to reserve resources. In the second phase, the coordinator captures the replies from all databases. If the response is yes, the coordinator asks all databases to confirm the transaction. If any of the databases respond as no, the coordinator asks all databases to cancel the transaction.
  • Saga: It’s an asynchronous way to achieve the transaction. It’s an event driven process. Micro-services generally use Saga as their default choice. In Saga, all operations are executed in a sequence. When one operation finishes, then the next operation is executed. For the rollback purpose, we need to prepare double operations: one for execution and the another one for the rollback. To coordinate operations in Saga, there are two ways:
    • Choreography: All services do their jobs by subscribing to other services’ events. This is a decentralized coordination.
    • Orchestration: In this way, there is a single coordinator to instruct all services in a defined order.