XOps  Platform Engineering  Site Reliability Engineering  DevSecOps  Data ops

Unlocking the
power of XOps

In today’s ever-evolving tech landscape, Extended Operations (XOps) have become the driving force behind operational excellence. At Optimized, we recognize the critical importance of XOps in integrating DevOps, Platform Engineering, SRE, MLOps, FinOps, and DevSecOps. Our comprehensive offering empowers you to harness the full potential of these interconnected disciplines, providing insights to maximize engineering effciency, foster collaboration by breaking down silos, all while prioritizing cost optimization in the dynamic tech landscape.

PLATFORM ENGINEERING

Containerization

Employing containers (e.g. Docker) for consistent application packaging and deployment across diverse environments

Serverless Computing

Leveraging serverless platforms for code execution without infrastructure management.

Orchestration

Managing containerized applications and resources at scale (e.g., Kubernetes).

Infrastructure Automation

Automating the provisioning and management of infrastructure resources.

PLATFORM ENGINEERING

Containerization

Employing containers (e.g. Docker) for consistent application packaging and deployment across diverse environments

Serverless Computing

Leveraging serverless platforms for code execution without infrastructure management.

Orchestration

Managing containerized applications and resources at scale (e.g., Kubernetes).

Infrastructure Automation

Automating the provisioning and management of infrastructure resources.

DEVOPS

Continuous Integration:

Automating code integration and testing to ensure seamless merges.

Continuous Deployment:

Automating code deployment to acheive faster, more reliable releases.

Infrastructure as Code:

Treating infrastructure configurations as code for consistent, automated provisioning.

Collaboration:

Fostering close collaboration between teams to break down silos and improve efficiency.

MACHINE LEARNING OPERATIONS (MLOPS)

Data Management

Efficiently storing, processing and managing large volumes of data for machine learning purposes

Model Development

Streamlining the machine learning model development, training and evaluation processes

Model Deployment

Automating the deployment of machine learning models into production environments

Monitoring and Governance

Continuously monitoring models, data quality and performance while emphasizing ethical and compliant AI.

SITE RELIABILITY ENGINEERING (SRE)

Reliability Engineering

Focusing on designing and maintaining systems to meet specific reliability goals, often defined by service level objectives (SLOs).

Incident Management

Establishing procedures and playbooks for incident response and mitigatio

Monitoring and Alerting

Implementing robust monitoring and alerting systems for incident detection and response.

Error Budgeting

Setting error and downtime thresholds, managing system changes accordingly

Reliability Engineering

Focusing on designing and maintaining systems to meet specific reliability goals, often defined by service level objectives (SLOs).

Incident Management

Establishing procedures and playbooks for incident response and mitigatio

Monitoring and Alerting

Implementing robust monitoring and alerting systems for incident detection and response.

Error Budgeting

Setting error and downtime thresholds, managing system changes accordingly

DEVSECOPS

Incident Response

The foundation that supports cost management in the cloud. FinOps combines financial accountability with the agile nature of cloud computing, enabling real-time decision-making and organizational alignment.

Compliance and Governance

Serving as the canopy, TBM provides the strategic framework for running IT like a business, focusing on value creation, cost efficiency, and alignment with business goals.

Security integration

Integrating security practices and automation into the DevOps pipeline to ensure security is a primary consideration.

Security testing

Conducting security testing, vulnerability scanning, and code analusis as integral parts of the CI/CD process.

DataOps

Data Ingestion

Data Ingestion Efficiently collecting, integrating, and processing data from various sources into a unified data ecosystem.

Data Quality

Data Quality Management Implementing processes and tools to monitor, profile, and ensure data integrity and trustworthiness throughout its lifecycle.

Data Orchestration

Data Orchestration Managing and automating the flow of data across disparate systems, enabling seamless data movement and transformations.

Data Governance

Data Governance Establishing policies, standards, and controls to ensure data security, compliance, and effective data management practices.
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