| Case Study

What is Shakudo - The Operating System for Data Stacks

Unlock your data team's potential and use the best-of-breed data tools on your data stack with Shakudo. Read more about how Shakudo enables your team to streamline data transformation, optimize cloud cost, and automate DevOps tasks.

What is Shakudo - The Operating System for Data Stacks

Author(s):
Sabrina Aquino
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Updated on:
May 19, 2023
in
Product

Table of contents

Overview 

In the ever-evolving landscape of data science, the founders of Shakudo observed a common roadblock in many organizations - brilliant ideas often never made it into production due to a lack of DevOps engineering resources. Shakudo emerged from the need for a robust solution to this challenge, providing a user-friendly operating system for data stacks.

Why Shakudo?

Shakudo’s mission is to empower data teams by eliminating the complexity of managing their data stack, allowing for the effective implementation of their ideas through: 

Effortless Customized Stack

Build a stack that works precisely for your company without worrying about maintenance costs or stability.

Comprehensive Single UI with Automated DevOps

Collaborate on the entire data stack through a single UI, manage access and monitor cost. Reconcile partially overlapping state of tools into a single consistent global state with automated DevOps.

Cloud Cost Optimization

Significantly reduce cloud cost with Shakudo cloud compute management and autoscaling.

Core Platform Components

Shakudo offers a comprehensive data ecosystem that is continually expanding to include a diverse range of best-of-breed tools and technologies. The Platform ensures that your organization is equipped with the most up-to-date data management solutions. Here's how it achieves this goal through its core components:

Sessions: A unified development environment that simplifies the setup process, enabling data teams to start building right away without worrying about environment configuration. This immediate readiness to build enhances productivity and reduces downtime.

Jobs and Services: Whether it's data cleaning in the middle of the night or real-time data updates throughout the day, Jobs ensures your data processing runs smoothly and efficiently. Services take care of deploying features like dashboards, websites, or APIs. Both features offer flexible deployment options, using GIT repositories or pre-built Docker images, and can be scheduled or triggered as required. This orchestration capability means your data teams can manage their workflows more effectively and react quickly to changing requirements.

Shakudo Stack Components: A universe of pre-configured, fully-connected data stacks supporting end-to-end use cases of data and machine learning applications. This feature reduces the time and effort required to setup and connect data stack components, accelerating your path to data insights.

Building a Complete Data Stack Universe

Shakudo is dedicated to building a complete and ever-growing universe of data stack components. It ensures your organization always has access to best-of-breed tools and technologies and the list of integrations is continuously updated to keep up with the fast-paced changes in the data world. You can check out the latest additions on our integrations page.

When to Use Shakudo

Shakudo's platform is adaptable and caters to a diverse range of problems and requirements. Whether you want to quickly develop models, deploy pipelines, monitor model performance, or build data applications, Shakudo provides the right tools and user-friendly environment for your needs.

As your organization grows and your data needs become more complex, Shakudo helps you scale your data infrastructure with ease. For teams eager to explore emerging data technologies or test new tools, it offers a supportive, easy-to-navigate environment. 

The Platform designed to support various tools and use cases, including:

Data Engineering: Streamline data transformation development and deployment processes for efficient data management with:

  • dbt (Data Transformation)
  • Apache Airflow, Prefect, or Dagster (Pipeline Orchestration)
  • Airbyte (Data Integration)
  • Add open source data warehouse tools like Hudi, Iceberge
  • Add distributed sql engine like Trino, Apache Spark¬†¬†
  • Add streaming like Kafka, Flink

Distributed Computing: Manage data larger than memory, optimizing data processing and storage capabilities with: 

  • Dask¬† (Distributed Computing)
  • Apache Spark (Large-scale Data Processing)
  • Ray (distributed model training and fine tuning)

Data analytics and Visualization: Enhance data insights and decision-making with advanced analytics and visualization with: 

  • Superset, Cube.dev, Metabase (BI Dashboard)
  • Streamlit (python based dashboarding tool)

Deployment of Batch Jobs: Automate and manage batch jobs efficiently for improved data processing with:

  • Apache Airflow, Prefect, or Dagster (Pipeline Orchestration)
  • Jenkins (Pipeline Automation)

Serving Data Applications and Pipelines: Seamlessly serve and manage data applications and pipelines for better data flow and accessibility with:

  • Django, FastAPI, or Flask (Web Framework)

Machine Learning Model Training: Train machine learning models effectively, ensuring optimal performance and results with:

  • TensorFlow, PyTorch, or MXNet (Deep¬† Learning Framework)
  • Scikit-Learn, XGBoost, or LightGBM (Machine Learning Libraries)
  • AutoGluon (AutoML)

Machine Learning Model Serving: Deploy and manage machine learning models for production, providing reliable and efficient solutions with:

  • NVIDIA Triton (Model Serving)
  • TFServe

Connection to storage and data warehousing: As your organization grows and the volume of data increases, Shakudo can help scale your data infrastructure to accommodate the increasing workload with:

  • Amazon S3, Google Storage Bucket, or Azure Blob Storage (storage )
  • Snowflake, BigQuery, or Amazon Redshift (Data Warehouse)

Experimenting with New Data Tools: If your team wants to explore emerging data technologies or test new tools without the burden of DevOps overhead, Shakudo allows for easy experimentation in a flexible environment with:

  • Langchain¬†
  • Stanford Alpaca or flan-ul2 (Open source Large Language Models)

In Conclusion 

Shakudo is not only an operating system for your data stack but also a strategic partner on your data management journey. The Platform equips your team with the tools needed to innovate and excel in today's data-driven world.

As your organization grows and your data needs evolve, Shakudo scales with you, ensuring your data infrastructure can handle increasing workloads and complexity. To experience the transformative impact of Shakudo's platform, contact our team today.

Sabrina Aquino

Sabrina is a creative Software Developer who has managed to create a huge community by sharing her personal experiences with technologies and products. A great problem solver, an above average Age of Empires II player and a mediocre Linux user. Sabrina is currently an undergraduate in Computer Engineering at UFRN (Federal University of Rio Grande do Norte).
| Case Study
What is Shakudo - The Operating System for Data Stacks

Key results

Data Stack

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Overview 

In the ever-evolving landscape of data science, the founders of Shakudo observed a common roadblock in many organizations - brilliant ideas often never made it into production due to a lack of DevOps engineering resources. Shakudo emerged from the need for a robust solution to this challenge, providing a user-friendly operating system for data stacks.

Why Shakudo?

Shakudo’s mission is to empower data teams by eliminating the complexity of managing their data stack, allowing for the effective implementation of their ideas through: 

Effortless Customized Stack

Build a stack that works precisely for your company without worrying about maintenance costs or stability.

Comprehensive Single UI with Automated DevOps

Collaborate on the entire data stack through a single UI, manage access and monitor cost. Reconcile partially overlapping state of tools into a single consistent global state with automated DevOps.

Cloud Cost Optimization

Significantly reduce cloud cost with Shakudo cloud compute management and autoscaling.

Core Platform Components

Shakudo offers a comprehensive data ecosystem that is continually expanding to include a diverse range of best-of-breed tools and technologies. The Platform ensures that your organization is equipped with the most up-to-date data management solutions. Here's how it achieves this goal through its core components:

Sessions: A unified development environment that simplifies the setup process, enabling data teams to start building right away without worrying about environment configuration. This immediate readiness to build enhances productivity and reduces downtime.

Jobs and Services: Whether it's data cleaning in the middle of the night or real-time data updates throughout the day, Jobs ensures your data processing runs smoothly and efficiently. Services take care of deploying features like dashboards, websites, or APIs. Both features offer flexible deployment options, using GIT repositories or pre-built Docker images, and can be scheduled or triggered as required. This orchestration capability means your data teams can manage their workflows more effectively and react quickly to changing requirements.

Shakudo Stack Components: A universe of pre-configured, fully-connected data stacks supporting end-to-end use cases of data and machine learning applications. This feature reduces the time and effort required to setup and connect data stack components, accelerating your path to data insights.

Building a Complete Data Stack Universe

Shakudo is dedicated to building a complete and ever-growing universe of data stack components. It ensures your organization always has access to best-of-breed tools and technologies and the list of integrations is continuously updated to keep up with the fast-paced changes in the data world. You can check out the latest additions on our integrations page.

When to Use Shakudo

Shakudo's platform is adaptable and caters to a diverse range of problems and requirements. Whether you want to quickly develop models, deploy pipelines, monitor model performance, or build data applications, Shakudo provides the right tools and user-friendly environment for your needs.

As your organization grows and your data needs become more complex, Shakudo helps you scale your data infrastructure with ease. For teams eager to explore emerging data technologies or test new tools, it offers a supportive, easy-to-navigate environment. 

The Platform designed to support various tools and use cases, including:

Data Engineering: Streamline data transformation development and deployment processes for efficient data management with:

  • dbt (Data Transformation)
  • Apache Airflow, Prefect, or Dagster (Pipeline Orchestration)
  • Airbyte (Data Integration)
  • Add open source data warehouse tools like Hudi, Iceberge
  • Add distributed sql engine like Trino, Apache Spark¬†¬†
  • Add streaming like Kafka, Flink

Distributed Computing: Manage data larger than memory, optimizing data processing and storage capabilities with: 

  • Dask¬† (Distributed Computing)
  • Apache Spark (Large-scale Data Processing)
  • Ray (distributed model training and fine tuning)

Data analytics and Visualization: Enhance data insights and decision-making with advanced analytics and visualization with: 

  • Superset, Cube.dev, Metabase (BI Dashboard)
  • Streamlit (python based dashboarding tool)

Deployment of Batch Jobs: Automate and manage batch jobs efficiently for improved data processing with:

  • Apache Airflow, Prefect, or Dagster (Pipeline Orchestration)
  • Jenkins (Pipeline Automation)

Serving Data Applications and Pipelines: Seamlessly serve and manage data applications and pipelines for better data flow and accessibility with:

  • Django, FastAPI, or Flask (Web Framework)

Machine Learning Model Training: Train machine learning models effectively, ensuring optimal performance and results with:

  • TensorFlow, PyTorch, or MXNet (Deep¬† Learning Framework)
  • Scikit-Learn, XGBoost, or LightGBM (Machine Learning Libraries)
  • AutoGluon (AutoML)

Machine Learning Model Serving: Deploy and manage machine learning models for production, providing reliable and efficient solutions with:

  • NVIDIA Triton (Model Serving)
  • TFServe

Connection to storage and data warehousing: As your organization grows and the volume of data increases, Shakudo can help scale your data infrastructure to accommodate the increasing workload with:

  • Amazon S3, Google Storage Bucket, or Azure Blob Storage (storage )
  • Snowflake, BigQuery, or Amazon Redshift (Data Warehouse)

Experimenting with New Data Tools: If your team wants to explore emerging data technologies or test new tools without the burden of DevOps overhead, Shakudo allows for easy experimentation in a flexible environment with:

  • Langchain¬†
  • Stanford Alpaca or flan-ul2 (Open source Large Language Models)

In Conclusion 

Shakudo is not only an operating system for your data stack but also a strategic partner on your data management journey. The Platform equips your team with the tools needed to innovate and excel in today's data-driven world.

As your organization grows and your data needs evolve, Shakudo scales with you, ensuring your data infrastructure can handle increasing workloads and complexity. To experience the transformative impact of Shakudo's platform, contact our team today.

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