Verified Service Provider in Angola
Bioinformatics Infrastructure in Angola
Engineering Excellence & Technical Support
Bioinformatics Infrastructure solutions for Digital & Analytical. High-standard technical execution following OEM protocols and local regulatory frameworks.
High-Performance Computing Cluster Deployed
A cutting-edge High-Performance Computing (HPC) cluster has been successfully deployed and is now operational, significantly accelerating genomic sequencing, structural biology analysis, and complex data simulations for Angolan researchers.
Centralized Bioinformatics Data Repository Established
A secure and scalable cloud-based data repository has been implemented, providing a centralized platform for storing, managing, and sharing large-scale biological datasets, fostering collaboration and data accessibility across Angolan institutions.
Bioinformatics Pipeline Automation Framework Deployed
A robust automation framework for common bioinformatics pipelines has been deployed, enabling researchers to efficiently process and analyze genomic, transcriptomic, and proteomic data with standardized and reproducible workflows, reducing turnaround times and increasing analytical throughput.
What Is Bioinformatics Infrastructure In Angola?
Bioinformatics infrastructure in Angola refers to the integrated set of computational resources, databases, software tools, networks, and skilled personnel necessary for the storage, analysis, interpretation, and dissemination of biological data. This infrastructure underpins research and development in various life science disciplines by enabling the processing of large-scale biological datasets, such as genomic, proteomic, transcriptomic, and metabolomic information. Its primary goal is to facilitate high-throughput data analysis, predictive modeling, and the generation of actionable insights for scientific discovery and application. The establishment and maintenance of robust bioinformatics infrastructure are critical for Angola to participate effectively in global biological research, address national health priorities, and foster innovation in areas like agriculture, disease surveillance, and biodiversity conservation.
| Stakeholder Group | Needs/Rationale | Typical Use Cases |
|---|---|---|
| Academic and Research Institutions | Facilitate novel scientific discovery, publish high-impact research, secure funding, and train future scientists. Enable complex data analysis for genomics, transcriptomics, proteomics, and evolutionary studies. | Genome sequencing and assembly of local flora and fauna; identification of disease-causing pathogens; development of diagnostic tools; understanding genetic basis of local crop traits; biodiversity cataloging; evolutionary studies. |
| Public Health Sector (Ministries of Health, National Institutes of Health) | Enhance disease surveillance, outbreak investigation, diagnostics, and drug discovery. Support the development of personalized medicine approaches and understand disease epidemiology. | Genomic surveillance of infectious diseases (e.g., malaria, HIV, COVID-19); identification of antimicrobial resistance genes; development of rapid diagnostic tests; phylogenetic analysis of pathogen spread; pharmacogenomic studies for drug efficacy. |
| Agricultural Sector (Ministries of Agriculture, Research Centers) | Improve crop and livestock breeding, enhance food security, and manage agricultural pests and diseases. Enable the development of climate-resilient and high-yield varieties. | Marker-assisted selection for improved crop traits (drought tolerance, disease resistance); genomic selection in livestock; identification of genes for enhanced nutritional value; pest and pathogen identification and control strategies; soil microbiome analysis. |
| Environmental Agencies and Biodiversity Conservation Organizations | Monitor biodiversity, track endangered species, understand ecosystem health, and manage natural resources. Support conservation efforts and ecological research. | DNA barcoding for species identification; population genetics studies for conservation; metagenomic analysis of environmental samples (soil, water); tracking invasive species; assessing the impact of climate change on biodiversity. |
| Biotechnology and Pharmaceutical Companies (emerging) | Support drug discovery and development, diagnostic kit manufacturing, and the development of bio-based products. Foster innovation and commercialization of biological discoveries. | Target identification for drug development; biomarker discovery; development of molecular diagnostics; bioprocess optimization; strain engineering for industrial applications. |
Key Components of Bioinformatics Infrastructure
- High-performance computing (HPC) clusters and cloud computing platforms for large-scale data processing.
- Secure and scalable data storage solutions (e.g., SAN, NAS, object storage) for housing vast biological datasets.
- Specialized bioinformatics software suites and pipelines for sequence alignment, variant calling, gene expression analysis, phylogenetic reconstruction, and protein structure prediction.
- Access to public biological databases (e.g., NCBI, Ensembl, UniProt) and the development of curated national databases.
- High-speed network connectivity to enable efficient data transfer and remote access to resources.
- Data management systems and protocols for ensuring data integrity, reproducibility, and FAIR principles (Findable, Accessible, Interoperable, Reusable).
- Skilled personnel, including bioinformaticians, computational biologists, data scientists, and IT support staff, for system administration, tool development, and user support.
- Training and educational programs to build local capacity in bioinformatics.
Who Needs Bioinformatics Infrastructure In Angola?
Bioinformatics infrastructure is crucial for advancing research, healthcare, and agricultural development in Angola. It enables advanced data analysis, genomic sequencing, disease surveillance, and the development of novel biotechnologies. The demand for such infrastructure spans various sectors, each with specific needs and user groups. Identifying these target customers and their departmental affiliations is key to designing and implementing effective bioinformatics solutions.
| Target Customer Group | Key Departments/Units | Specific Needs/Applications |
|---|---|---|
| Academic and Research Institutions | Biology Departments, Biochemistry Departments, Genetics Departments, Public Health Research Centers, Agricultural Research Institutes | Genomic sequencing analysis, comparative genomics, transcriptomics, proteomics, phylogenetics, population genetics, molecular evolution studies, bioinformatics method development. |
| Healthcare Sector | Hospitals (Pathology, Infectious Diseases, Oncology, Genetics Clinics), Public Health Laboratories, National Reference Laboratories, Medical Schools | Diagnostic genomics (e.g., for inherited diseases, cancer), pathogen identification and surveillance, antimicrobial resistance tracking, outbreak investigation, personalized medicine initiatives, clinical trial data analysis. |
| Agricultural Sector | National Agricultural Research Institutes, Agronomy Departments, Veterinary Research Centers, Crop and Livestock Improvement Agencies | Genomic selection for improved crop varieties and livestock breeds, pest and disease resistance studies, marker-assisted selection, soil microbiome analysis, environmental genomics for sustainable agriculture. |
| Government and Public Health Agencies | Ministry of Health (Disease Surveillance Units, Epidemiological Centers), National Institute of Public Health, Ministry of Agriculture, Environmental Protection Agencies | National disease surveillance systems, real-time outbreak monitoring and response, public health policy development based on genetic data, environmental monitoring, biodiversity studies. |
| Biotechnology and Pharmaceutical Companies | Research and Development Departments, Drug Discovery Units, Quality Control Laboratories | Target identification for drug development, biomarker discovery, drug efficacy and safety studies, vaccine development, development of diagnostic kits, industrial biotechnology applications. |
Target Customers and Departments for Bioinformatics Infrastructure in Angola
- {"title":"Academic and Research Institutions","description":"These institutions form the backbone of scientific inquiry and require robust bioinformatics capabilities for cutting-edge research."}
- {"title":"Healthcare Sector","description":"Improving public health outcomes through advanced diagnostics, personalized medicine, and effective disease management is a primary driver."}
- {"title":"Agricultural Sector","description":"Enhancing food security and agricultural productivity through genetic improvement of crops and livestock, as well as disease control."}
- {"title":"Government and Public Health Agencies","description":"Supporting national health strategies, disease surveillance, and policy-making with data-driven insights."}
- {"title":"Biotechnology and Pharmaceutical Companies","description":"Facilitating drug discovery, development, and the creation of novel biotechnological products."}
Bioinformatics Infrastructure Process In Angola
The process of establishing and utilizing bioinformatics infrastructure in Angola, from an initial inquiry to the full execution of bioinformatics workflows, involves several key stages. This workflow is designed to address the growing need for computational biology resources to support research, diagnostics, and public health initiatives within the country. The initial inquiry typically comes from researchers, academic institutions, government health agencies, or funding bodies seeking to leverage bioinformatics for their projects. This leads to a formalization phase where needs are assessed, resources are identified, and a project plan is developed. Subsequently, the infrastructure is either built or accessed, followed by the development and execution of specific bioinformatics pipelines and analyses. Finally, results are interpreted, reported, and used to inform further research or policy decisions.
| Stage | Description | Key Activities | Responsible Parties | Potential Challenges |
|---|---|---|---|---|
| Inquiry & Needs Assessment | Initial identification of the need for bioinformatics support and a detailed understanding of the specific research or health questions that require computational analysis. | Submitting proposals, holding consultation meetings, identifying research gaps, defining project scope, evaluating existing computational capacity. | Researchers, Principal Investigators, Government Health Agencies, Academic Institutions, Funding Bodies. | Lack of awareness about bioinformatics capabilities, unclear project objectives, difficulty in articulating specific computational needs. |
| Planning & Resource Allocation | Developing a comprehensive plan for establishing or accessing bioinformatics infrastructure, including defining technical requirements, budget, and timelines. | Securing funding, identifying suitable hardware and software, establishing partnerships (national/international), defining data management policies, hiring personnel. | Project Managers, IT Specialists, Bioinformatics Scientists, Institutional Leadership, Funding Agencies. | Securing adequate funding, limited availability of skilled personnel, bureaucratic hurdles in procurement, establishing reliable internet connectivity. |
| Infrastructure Development/Access | Setting up or gaining access to the necessary computational resources, including high-performance computing (HPC) clusters, cloud computing services, and specialized software. | Procuring and installing hardware, setting up software environments, establishing user access protocols, training users, ensuring data security and privacy. | IT Department, Bioinformatics Specialists, System Administrators, External Vendors/Cloud Providers. | High initial investment costs, maintenance and upgrade requirements, limited local technical expertise for complex infrastructure management, power supply instability. |
| Workflow Design & Implementation | Developing and implementing specific bioinformatics pipelines and analytical workflows tailored to the project's requirements. | Selecting appropriate algorithms and tools, scripting and programming, version control, testing and validation of pipelines, data standardization. | Bioinformatics Scientists, Data Analysts, Researchers. | Lack of standardized workflows, choosing the right tools for specific datasets, ensuring reproducibility, managing large datasets. |
| Data Analysis & Interpretation | Executing the designed workflows on research data, analyzing the output, and interpreting the biological or health implications of the findings. | Running pipelines, quality control of results, statistical analysis, visualization of data, generating biological insights, collaborating with domain experts. | Bioinformatics Scientists, Researchers, Clinicians, Biologists. | Interpreting complex data, identifying meaningful patterns, potential for false positives/negatives, need for interdisciplinary collaboration. |
| Reporting & Dissemination | Documenting the findings, preparing reports, publications, and presentations to share the results with stakeholders and the scientific community. | Writing scientific papers, creating presentations, contributing to project reports, presenting at conferences, sharing data (where appropriate). | Researchers, Bioinformatics Scientists, Communication Officers. | Ensuring clear and accurate communication of complex technical findings, publication delays, accessibility of research findings. |
| Sustainability & Future Development | Ensuring the long-term viability of the bioinformatics infrastructure and planning for future upgrades and expansion based on evolving needs and technological advancements. | Securing ongoing funding, continuous training and capacity building, regular infrastructure maintenance and upgrades, fostering a national bioinformatics community, developing national strategies. | Institutional Leadership, Government Agencies, Funding Bodies, National Bioinformatics Consortia. | Securing long-term operational funding, adapting to rapid technological changes, brain drain of skilled personnel, fostering international collaboration for continued support. |
Bioinformatics Infrastructure Process in Angola
- Inquiry & Needs Assessment
- Planning & Resource Allocation
- Infrastructure Development/Access
- Workflow Design & Implementation
- Data Analysis & Interpretation
- Reporting & Dissemination
- Sustainability & Future Development
Bioinformatics Infrastructure Cost In Angola
The cost of bioinformatics infrastructure in Angola is influenced by several key pricing factors. These include the type of hardware and software required, the scale and complexity of the research or operational needs, the level of technical support and maintenance, licensing fees for specialized software, and internet connectivity and data storage solutions. Procurement processes and the availability of local vendors also play a significant role. As Angola's technological landscape evolves, prices can fluctuate. Specific cost ranges are difficult to pinpoint precisely without detailed project specifications, but general estimations can be provided for common components. Import duties and taxes can also add to the overall cost. Furthermore, the need for specialized training for personnel to manage and utilize the infrastructure contributes to the total investment.
| Infrastructure Component | Estimated Cost Range (Angolan Kwanza - AOA) | Notes/Assumptions |
|---|---|---|
| High-Performance Computing (HPC) Server (Entry-level, 1-2 GPUs) | 10,000,000 - 30,000,000 | Prices vary based on processing power, RAM, and GPU configuration. Includes basic OS. |
| Workstation (Bioinformatics-ready, high-end) | 3,000,000 - 8,000,000 | Suitable for individual researchers or smaller labs. Configurable for specific analysis needs. |
| Network Attached Storage (NAS) (10-20TB capacity) | 1,500,000 - 4,000,000 | Cost depends on speed, redundancy, and number of drive bays. |
| Bioinformatics Software Suite License (Annual Subscription, e.g., Geneious, CLC Genomics Workbench - per user) | 500,000 - 1,500,000 | Prices are highly variable based on the software vendor and its capabilities. Open-source alternatives exist. |
| Cloud Computing (e.g., AWS, Azure, GCP - monthly usage for moderate compute) | 200,000 - 800,000+ | Highly dependent on actual usage, instance types, and data transfer. Can be more cost-effective for variable workloads. |
| High-Speed Internet Connectivity (Dedicated line, business grade) | 100,000 - 300,000 per month | Requires assessment of available providers and required bandwidth. Crucial for data transfer and remote access. |
| Annual Maintenance Contract (for HPC/servers) | 1,000,000 - 5,000,000+ | Typically a percentage of the hardware cost, covering hardware replacement and technical support. |
| Personnel Training (Basic Bioinformatics Tools) | 300,000 - 1,000,000 per participant | Depends on the duration, content, and trainer's expertise. Can be conducted locally or remotely. |
Key Pricing Factors for Bioinformatics Infrastructure in Angola
- Hardware Acquisition (Servers, Workstations, Storage)
- Software Licensing (Operating Systems, Bioinformatics Tools, Databases)
- Cloud Computing Services (if applicable)
- Network Infrastructure and Internet Bandwidth
- Data Storage Solutions (On-premise or Cloud)
- Technical Support and Maintenance Contracts
- Personnel Training and Skill Development
- Import Duties and Taxes
- Installation and Setup Costs
- Power and Cooling for Data Centers
Affordable Bioinformatics Infrastructure Options
Securing robust bioinformatics infrastructure is crucial for research and development, but budget constraints are a common challenge. Fortunately, a range of affordable options exist, often focusing on maximizing value through strategic bundling and cost-saving measures. This involves understanding your specific needs and leveraging solutions that offer flexibility and scalability without unnecessary overhead. The key is to identify 'value bundles' – packages of services or resources that are more cost-effective when purchased together – and to implement smart cost-saving strategies across your infrastructure.
| Infrastructure Type | Potential Value Bundle | Cost-Saving Strategy | Typical Use Case |
|---|---|---|---|
| Cloud Computing | Compute, Storage, Networking, Managed Services | Reserved Instances, Spot Instances, Savings Plans, Auto-Scaling | Genomic sequencing analysis, large-scale simulations, temporary high-demand projects |
| On-Premises HPC | Compute clusters, specialized hardware (GPUs) | Shared resource allocation, energy-efficient hardware, long-term depreciation planning | Constant, high-volume computational tasks, data sovereignty requirements |
| Software | Analysis pipelines, visualization tools, database management systems | Open-source alternatives, academic licenses, site licenses | Primary data analysis, drug discovery, population genetics |
| Storage | Object storage, block storage, file storage | Tiered storage (hot, cold, archive), data compression, cloud storage tiering | Raw sequencing data, experimental results, long-term archiving |
| Networking | High-speed interconnects, VPN services | Optimized data transfer protocols, leased lines for predictable traffic | Data transfer between compute and storage, remote access to resources |
Key Value Bundles and Cost-Saving Strategies
- Cloud Computing as a Service (CCaaS) with Reserved Instances/Savings Plans: Leveraging cloud providers' pre-paid compute resources offers significant discounts compared to on-demand pricing. This is ideal for predictable workloads.
- Open-Source Software Suites: Utilizing free and open-source tools for analysis, visualization, and data management drastically reduces licensing fees. Many robust, industry-standard bioinformatics pipelines are built on these.
- Managed Bioinformatics Platforms: These often bundle compute, storage, pre-installed software, and sometimes even specialized expertise, offering a streamlined and potentially cost-effective solution for organizations that lack in-house IT support.
- Shared Infrastructure and Collaborative Resources: Pooling resources with other institutions or participating in national/regional bioinformatics consortia can spread the cost of high-performance computing (HPC) and specialized equipment.
- Containerization and Orchestration (e.g., Docker, Kubernetes): While an initial learning curve, these technologies optimize resource utilization, making existing hardware or cloud instances more efficient and reducing wasted capacity.
- Tiered Storage Solutions: Storing frequently accessed data on high-speed storage and less critical data on cheaper, archival storage significantly reduces overall storage costs.
- 'Pay-as-you-go' Models: Cloud services allow for scaling up or down based on demand, avoiding the upfront capital investment of on-premises hardware that might sit idle.
- Community Support and Forums: Engaging with active open-source communities can provide free troubleshooting and valuable insights, reducing reliance on expensive commercial support contracts.
- Utilizing Academic or Non-Profit Discounts: Many software vendors and cloud providers offer special pricing for educational and research institutions.
- Automation and Workflow Management Tools: Streamlining repetitive tasks reduces manual effort and computational time, leading to overall cost savings.
- Data Compression and Deduplication: Effective data management techniques can significantly reduce storage requirements, a major cost driver.
Verified Providers In Angola
In Angola, ensuring access to quality healthcare is paramount. When seeking medical services, partnering with verified providers is crucial for peace of mind and effective treatment. Franance Health stands out as a premier network of credentialed healthcare professionals and facilities across Angola. Their rigorous vetting process and commitment to excellence make them the definitive choice for reliable and high-standard medical care. This document outlines why Franance Health credentials signify the best choice for your health needs in Angola.
| Credential Aspect | Franance Health Verification | Benefit to Patients |
|---|---|---|
| Medical Licenses | All listed physicians and specialists hold valid and current Angolan medical licenses. | Guarantees legal and authorized practice of medicine. |
| Board Certifications | Verification of specialists holding recognized board certifications in their respective disciplines. | Ensures advanced training and expertise in specific medical areas. |
| Educational Background | Comprehensive review of medical school and postgraduate training. | Confirms foundational knowledge and academic rigor. |
| Clinical Experience | Assessment of practical experience and tenure in medical practice. | Indicates practical application of knowledge and skills. |
| Facility Accreditation | Hospitals and clinics are accredited by relevant national or international bodies. | Confirms adherence to safety, quality, and operational standards. |
| Professional References | Checks with professional peers and institutions. | Provides an external validation of competence and character. |
| Background Checks | Screening for any disciplinary actions or legal issues. | Upholds ethical standards and patient trust. |
Why Franance Health Credentials Represent the Best Choice:
- Rigorous Vetting Process: Franance Health employs a stringent selection methodology, ensuring all affiliated providers meet and exceed established quality benchmarks.
- Certified Professionals: Credentials verify that practitioners possess the necessary education, licenses, and specialized training required for their respective fields.
- Accredited Facilities: Affiliated hospitals and clinics undergo thorough inspections to confirm adherence to safety, hygiene, and operational standards.
- Commitment to Ethical Practice: Franance Health prioritizes providers who demonstrate a strong commitment to ethical conduct and patient-centered care.
- Continuous Quality Improvement: The network actively monitors and encourages ongoing professional development and adherence to best practices among its members.
- Patient Safety Focus: All credentialing processes are designed with patient well-being and safety as the primary concern.
- Access to Specialized Care: Franance Health's extensive network provides access to a wide range of medical specialties, ensuring comprehensive coverage for diverse health needs.
- Enhanced Trust and Reliability: A Franance Health credential acts as a seal of trust, assuring patients they are receiving care from reputable and qualified sources.
- Streamlined Healthcare Navigation: By partnering with Franance Health, individuals and organizations can confidently navigate the Angolan healthcare landscape.
- Alignment with International Standards: Franance Health's credentialing often aligns with recognized international healthcare quality standards, further solidifying its credibility.
Scope Of Work For Bioinformatics Infrastructure
This document outlines the Scope of Work (SOW) for the establishment and maintenance of a robust bioinformatics infrastructure. It details the technical deliverables and standard specifications required to support advanced genomic and proteomic data analysis for research and development activities. The infrastructure will encompass computational resources, data storage, software tools, and network connectivity, designed for scalability, security, and ease of use.
| Component | Standard Specification | Description | Deliverable |
|---|---|---|---|
| Compute Nodes | x86-64 architecture, minimum 64 cores per node, 256GB RAM per node, high-speed interconnect (e.g., InfiniBand, 100GbE) | Dedicated servers for computationally intensive tasks like sequence alignment, variant calling, and genome assembly. | Configured and tested HPC cluster. |
| Storage System | Minimum 500TB usable capacity, RAID 6 or equivalent for data redundancy, 10GbE or higher network interface, support for NFS/SMB and/or S3 API | Centralized storage for raw sequencing data, processed data, and analysis results. | Deployed and integrated storage solution. |
| Operating System | Linux distribution (e.g., CentOS Stream, Ubuntu LTS) with LTS support | Foundation for all bioinformatics software and applications. | Standardized OS image deployed across compute nodes. |
| Job Scheduler | Slurm Workload Manager or equivalent | Manages and schedules jobs on the HPC cluster, optimizing resource utilization. | Configured and functional job scheduler. |
| Containerization Platform | Docker, Singularity | Enables reproducible and portable bioinformatics workflows. | Installed and configured container runtime. |
| Workflow Management System | Nextflow, Snakemake | Facilitates the creation, execution, and management of complex bioinformatics pipelines. | Installed and demonstrated basic pipeline execution. |
| Bioinformatics Software | Latest stable versions of commonly used tools (e.g., BWA, GATK, STAR, HISAT2, samtools, bedtools, R/Bioconductor, Python libraries) | Core analytical capabilities for genomic and proteomic data processing. | Installed and tested core software suite. |
| Networking | High-speed internal network (10GbE minimum), secure external access with VPN | Ensures fast data transfer between storage and compute, and secure remote access. | Configured network infrastructure. |
| Security | Role-based access control (RBAC), regular security patching, encrypted data storage options | Protects sensitive research data and ensures compliance. | Implemented access control and security policies. |
| Monitoring | Prometheus/Grafana stack or equivalent for system metrics, Sentry or equivalent for application errors | Proactive identification of performance bottlenecks and potential issues. | Deployed and configured monitoring dashboards. |
Key Technical Deliverables
- High-performance computing (HPC) cluster deployment and configuration.
- Scalable and secure data storage solution (e.g., NAS, object storage).
- Installation and management of a comprehensive suite of bioinformatics software (e.g., alignment tools, variant callers, genome assemblers, annotation pipelines).
- Containerization and workflow management system implementation (e.g., Docker, Singularity, Nextflow, Snakemake).
- Secure user access and authentication mechanisms.
- Data backup and disaster recovery strategy and implementation.
- Monitoring and alerting system for infrastructure health and performance.
- Documentation for infrastructure setup, user guides, and standard operating procedures (SOPs).
- Training for research staff on infrastructure utilization and best practices.
Service Level Agreement For Bioinformatics Infrastructure
This Service Level Agreement (SLA) outlines the guaranteed response times and uptime for the Bioinformatics Infrastructure provided by [Your Organization Name]. This SLA applies to all users with active accounts and approved access to the designated resources.
| Service Component | Uptime Guarantee | Response Time (Critical Incident) | Response Time (Major Incident) | Response Time (Minor Incident) | Scheduled Maintenance Notification |
|---|---|---|---|---|---|
| Core Compute Cluster (Scheduler, Nodes) | 99.5% | 1 hour | 4 hours | 8 business hours | 48 hours |
| Primary Data Storage (High-Performance File System) | 99.8% | 1 hour | 4 hours | 8 business hours | 48 hours |
| Network Connectivity (Internal & External Access) | 99.7% | 1 hour | 4 hours | 8 business hours | 48 hours |
| Core Bioinformatics Software Stack (OS, Common Libraries) | 99.5% | 2 hours | 8 business hours | 2 business days | 48 hours |
| User Support Desk (General Inquiries & Assistance) | N/A (Best Effort) | 4 business hours (acknowledgement) | 8 business hours (acknowledgement) | 2 business days (acknowledgement) | N/A |
Key Definitions
- Bioinformatics Infrastructure: Refers to the computing hardware, storage, network, and core bioinformatics software stacks (e.g., operating systems, schedulers, common libraries) managed and maintained by [Your Organization Name] for bioinformatics research.
- Critical Service Incident: An event that renders a significant portion or all of the Bioinformatics Infrastructure unusable, preventing users from performing core computational tasks. Examples include cluster-wide scheduler failure, loss of primary storage, or network outage affecting core services.
- Major Service Incident: An event that significantly degrades performance or impacts a substantial subset of users, making it difficult to perform essential computational tasks. Examples include slow cluster performance impacting job completion times for a majority of users, or failure of a specific key software module impacting a broad range of analyses.
- Minor Service Incident: An event that affects a limited number of users or services, causing minor inconvenience but not preventing core computational tasks. Examples include a single node failure, a specific application experiencing issues, or a request for user support not being immediately addressed.
- Downtime: Any period during which the Bioinformatics Infrastructure is unavailable to users due to scheduled maintenance or unscheduled incidents.
- Uptime: The percentage of time the Bioinformatics Infrastructure is available and functional.
- Response Time: The time taken by the support team to acknowledge and begin investigating a reported incident.
- Resolution Time: The time taken to restore service to a functional state after an incident is reported. This may not always mean full resolution but rather a mitigation to allow users to continue work.
In-Depth Guidance
Frequently Asked Questions
Phase 02: Execution
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