Bioinformatics Infrastructure in Mauritius
Engineering Excellence & Technical Support
Bioinformatics Infrastructure solutions for Digital & Analytical. High-standard technical execution following OEM protocols and local regulatory frameworks.
High-Performance Computing (HPC) Cluster Deployment
Established a state-of-the-art High-Performance Computing (HPC) cluster, providing researchers with unparalleled computational power for complex genomic analyses, large-scale simulations, and rapid data processing, accelerating the pace of discoveries in genetic research and agricultural science.
Secure Cloud-Based Data Repository
Implemented a secure, scalable, and geographically distributed cloud-based data repository, ensuring long-term preservation of sensitive genomic and biological datasets while facilitating seamless collaboration and data sharing among local and international research institutions.
Robust Bioinformatics Data Pipeline Integration
Developed and deployed robust, automated bioinformatics data pipelines, streamlining the processing of diverse biological data (e.g., next-generation sequencing, proteomics) from raw reads to actionable insights, reducing turnaround times and enhancing reproducibility of research findings.
What Is Bioinformatics Infrastructure In Mauritius?
Bioinformatics infrastructure in Mauritius refers to the integrated suite of computational resources, data management systems, software tools, and specialized expertise required to conduct advanced biological research, analysis, and discovery. This infrastructure underpins the ability of researchers, institutions, and industries within Mauritius to process, analyze, and interpret large-scale biological data generated from sources such as genomics, transcriptomics, proteomics, and metabolomics. It facilitates the application of computational approaches to address complex biological questions, drive innovation in life sciences, and support national priorities in health, agriculture, and environmental science.
| Who Needs Bioinformatics Infrastructure? | Typical Use Cases | |||
|---|---|---|---|---|
| Academic Research Institutions (Universities, Research Centers): Conducting fundamental and applied research in areas like molecular biology, genetics, disease mechanisms, and evolutionary biology. | Genomic data analysis: Sequencing and variant calling for research on genetic diseases, crop improvement, or microbial diversity. | Transcriptomic and proteomic analysis: Understanding gene expression patterns and protein interactions in response to stimuli or disease states. | Phylogenetic analysis: Studying evolutionary relationships of organisms and tracing disease outbreaks. | Drug discovery and development: Identifying potential drug targets and evaluating compound efficacy through in silico modeling. |
| Healthcare Providers and Hospitals: Improving diagnostics, personalized medicine, and public health surveillance. | Personalized medicine: Analyzing patient genomic data to tailor treatments for cancer, rare diseases, and pharmacogenomics. | Infectious disease surveillance and epidemiology: Tracking pathogen evolution, identifying outbreak sources, and developing diagnostic tools. | Diagnostic genomics: Identifying genetic causes of inherited disorders and predispositions to diseases. | |
| Agricultural Sector (Government Agencies, Private Companies): Enhancing crop productivity, disease resistance, and livestock management. | Crop breeding and improvement: Identifying genes for desirable traits like yield, drought tolerance, and pest resistance. | Livestock genomics: Improving breeding programs for enhanced productivity and disease resistance in animals. | Food safety and traceability: Analyzing microbial genomes to monitor foodborne pathogens and ensure quality. | |
| Environmental Science and Conservation Agencies: Monitoring biodiversity, assessing ecological impacts, and managing natural resources. | Biodiversity assessment: Using DNA barcoding and metagenomics to catalog species and understand ecosystem composition. | Environmental monitoring: Analyzing environmental DNA (eDNA) to track species presence and assess ecosystem health. | Bioremediation research: Identifying microbes with the potential to degrade pollutants. | |
| Biotechnology and Pharmaceutical Companies: Driving innovation in product development and research. | Bioprocess optimization: Analyzing microbial or cellular data to improve efficiency of industrial fermentation and production. | Biomarker discovery: Identifying molecular indicators for disease diagnosis, prognosis, or therapeutic response. | Development of novel bio-based products. |
Key Components of Bioinformatics Infrastructure:
- High-performance computing (HPC) clusters and cloud computing resources for data processing and simulation.
- Secure, scalable, and robust data storage solutions for raw and processed biological data.
- A comprehensive collection of bioinformatics software tools and databases (e.g., for sequence alignment, variant calling, phylogenetic analysis, pathway analysis).
- Data management platforms and pipelines for workflow automation, reproducibility, and collaborative research.
- Network connectivity and secure access protocols.
- Skilled bioinformatics personnel, including bioinformaticians, data scientists, and IT support specialists.
- Training and educational programs to develop local expertise.
Who Needs Bioinformatics Infrastructure In Mauritius?
The development of a robust bioinformatics infrastructure in Mauritius is not a luxury, but a strategic imperative for several key sectors. This infrastructure will empower researchers, businesses, and government agencies to leverage the power of biological data for innovation, disease control, economic growth, and environmental sustainability. Identifying the primary beneficiaries is crucial for targeted investment and resource allocation.
| Customer Segment | Key Needs and Applications | Example Departments/Organizations |
|---|---|---|
| Academic and Research Institutions | Genomic sequencing and analysis (human, plant, animal, microbial); Drug discovery and development; Personalized medicine research; Population genetics; Ecological and biodiversity studies; Bioinformatics training and education. | University of Mauritius (Faculty of Science, Faculty of Engineering); Mahatma Gandhi Institute; Research laboratories associated with teaching hospitals. |
| Healthcare Sector (Public and Private) | Diagnostic support for infectious diseases and genetic disorders; Epidemiological surveillance and outbreak response; Pharmacogenomics and personalized treatment strategies; Pathogen identification and tracking (e.g., for emerging diseases like Dengue, Chikungunya, or potential future pandemics); Public health data analysis. | Ministry of Health and Quality of Life (Public Health Laboratories, Epidemiology Unit, National Blood Transfusion Service); Private Hospitals and Clinics; Diagnostic Laboratories. |
| Agricultural Sector | Crop improvement and disease resistance breeding; Livestock health and productivity enhancement; Pest and disease management; Sustainable agricultural practices; Food safety and quality control; Aquaculture research. | Ministry of Agro-Industry and Food Security (Agricultural Research and Development Centres, Animal Health Division, Fisheries Division); Private agricultural enterprises; Sugar industry research institutions. |
| Biotechnology and Pharmaceutical Companies | Drug discovery and target identification; Biomarker discovery for diagnostics and prognostics; Development of novel biopharmaceuticals; Genomic and proteomic analysis for product development; Quality control and assurance. | Emerging local biotech startups; Existing pharmaceutical distributors looking to expand R&D; Companies involved in natural product extraction and development. |
| Environmental and Conservation Agencies | Biodiversity monitoring and assessment; Conservation genetics of endangered species; Environmental DNA (eDNA) analysis for species detection; Understanding microbial communities in ecosystems (soil, water); Climate change impact studies on flora and fauna. | Ministry of Environment, Solid Waste Management and Climate Change; National Parks and Conservation Service; Mauritius Research and Innovation Council (MRIC) - environmental research programs; NGOs focused on conservation. |
| Government Ministries and Regulatory Bodies | Evidence-based policy making in health, agriculture, and environment; Biosecurity and import/export regulation; Public health surveillance; Data standardization and management for national biological resources; National strategic planning for innovation and economic development. | Ministry of Finance, Economic Planning and Development; Prime Minister's Office; Mauritius Standards Bureau; Mauritius Research and Innovation Council (MRIC). |
Target Customers for Bioinformatics Infrastructure in Mauritius
- Academic and Research Institutions
- Healthcare Sector (Public and Private)
- Agricultural Sector
- Biotechnology and Pharmaceutical Companies
- Environmental and Conservation Agencies
- Government Ministries and Regulatory Bodies
Bioinformatics Infrastructure Process In Mauritius
The bioinformatics infrastructure process in Mauritius, from an initial inquiry to the execution of a bioinformatics project, generally follows a structured workflow. This workflow ensures that research needs are clearly understood, appropriate resources are allocated, and the project is completed efficiently and effectively. The process is designed to be collaborative, involving researchers, IT professionals, and potentially external stakeholders. This involves stages of understanding the request, planning the approach, acquiring and preparing data, performing analyses, interpreting results, and finally disseminating findings.
| Stage | Description | Key Activities | Responsible Parties | Output |
|---|---|---|---|---|
| Inquiry & Needs Assessment | Initial contact from a researcher or group requesting bioinformatics support. | Discuss research question, specific bioinformatics needs, data types, and expected outcomes. Define project scope and feasibility. | Researcher(s), Bioinformatics Support Staff, IT Infrastructure Team | Project proposal outline, initial understanding of requirements. |
| Resource Scoping & Planning | Determining the necessary computational resources, software, and expertise for the project. | Assess available infrastructure (servers, storage, cloud access), required software licenses, potential need for specialized tools or algorithms. Develop a detailed project plan with timelines and milestones. | Bioinformatics Support Staff, IT Infrastructure Team, Project Manager (if applicable) | Detailed project plan, resource allocation strategy, estimated timelines. |
| Data Acquisition & Preparation | Gathering and organizing the data for analysis. | Collect raw data from various sources (sequencers, databases, public repositories). Perform quality control (QC) checks, data cleaning, formatting, and transformation as needed. Ensure data privacy and security compliance. | Researcher(s), Bioinformatics Support Staff | Cleaned, QC'd, and formatted dataset(s) ready for analysis. |
| Analysis Execution | Performing the core bioinformatics analyses. | Run specified bioinformatics pipelines, algorithms, and statistical methods. This may involve scripting, using command-line tools, or graphical interfaces. Monitor job progress and troubleshoot any issues. | Bioinformatics Support Staff, Researcher(s) | Raw analysis results, intermediate outputs. |
| Result Interpretation & Validation | Making sense of the analysis outputs and ensuring their accuracy. | Interpret statistical significance, biological relevance, and patterns in the data. Validate findings using alternative methods or datasets. Collaborate with researchers to understand the biological context. | Researcher(s), Bioinformatics Support Staff | Interpreted results, validated findings, potential hypotheses. |
| Reporting & Dissemination | Communicating the project outcomes. | Generate reports, visualizations (graphs, figures), and summaries of the findings. Prepare data for publication, presentations, or grant applications. Ensure proper documentation of methods and results. | Researcher(s), Bioinformatics Support Staff | Project report, publications, presentations, visualizations. |
| Feedback & Iteration | Reviewing the project's success and identifying areas for improvement. | Gather feedback from researchers on the process and outcomes. Identify lessons learned for future projects. Archive data and code for reproducibility. Explore potential for further research or follow-up projects. | All involved parties | Project review, updated best practices, potential for new inquiries. |
Bioinformatics Infrastructure Process Workflow
- Inquiry & Needs Assessment
- Resource Scoping & Planning
- Data Acquisition & Preparation
- Analysis Execution
- Result Interpretation & Validation
- Reporting & Dissemination
- Feedback & Iteration
Bioinformatics Infrastructure Cost In Mauritius
Bioinformatics infrastructure in Mauritius, like globally, involves a complex interplay of hardware, software, data storage, and skilled personnel. The cost is not monolithic and depends heavily on the specific needs and scale of the operation, ranging from individual research projects to national-level initiatives. Several factors influence the pricing:
1. Hardware Acquisition:
- Computational Power: High-performance computing (HPC) clusters, servers, and powerful workstations are essential for processing large biological datasets. Costs vary significantly based on processing cores, RAM, and specialized hardware like GPUs.
- Storage Solutions: Robust and scalable storage is critical for genomic data, imaging, and other large datasets. Options include Network Attached Storage (NAS), Storage Area Networks (SAN), and cloud-based storage.
- Networking: High-speed internal and external networking is necessary for efficient data transfer within the infrastructure and to external resources.
2. Software Licensing:
- Commercial Software: Many powerful bioinformatics tools and platforms are proprietary and require substantial licensing fees, often on an annual basis. This can include genome assemblers, variant callers, visualization tools, and specialized analysis pipelines.
- Open-Source Software Maintenance: While many powerful tools are open-source, their effective deployment, integration, and ongoing maintenance often require skilled personnel and dedicated support, which has associated costs.
3. Cloud Computing Services:
- Pay-as-you-go Models: Cloud providers (AWS, Azure, Google Cloud) offer flexible computing and storage. Costs are determined by usage of CPU, memory, storage, and network transfer. This can be more cost-effective for variable workloads but can become expensive for sustained, high-demand usage.
4. Data Management and Storage:
- Data Volume: The sheer volume of biological data being generated is a primary cost driver.
- Data Redundancy and Backup: Implementing reliable backup and disaster recovery strategies adds to storage and operational costs.
5. Personnel and Expertise:
- Skilled Bioinformaticians: Recruiting and retaining highly skilled bioinformaticians, computational biologists, and IT support staff is a significant recurring cost, especially in a specialized field.
6. Maintenance and Support:
- Hardware and Software Updates: Ongoing maintenance contracts, software upgrades, and technical support are essential to ensure the infrastructure remains operational and secure.
Pricing Ranges in Mauritian Rupees (MUR):
It's challenging to provide exact figures without a detailed scope of work, but we can offer indicative ranges for common components. These are estimates and can fluctuate significantly based on vendor, negotiation, and specific configurations. For comparison, international prices are often converted to MUR, but local availability, import duties, and supplier markups can influence local pricing.
- Entry-level Server/Workstation for individual research: MUR 150,000 - MUR 500,000 (for powerful workstations capable of some local analysis).
- Small to Medium Cluster (e.g., 10-20 compute nodes): MUR 2,000,000 - MUR 10,000,000+ (depending on compute power, RAM, and storage).
- High-capacity Storage (e.g., 100 TB NAS): MUR 300,000 - MUR 1,500,000+.
- Annual Commercial Software Licenses: Varies wildly. Basic analytical suites might start from MUR 50,000 per year, while comprehensive enterprise-level platforms can be in the millions of MUR annually.
- Cloud Computing (Indicative monthly for moderate usage): MUR 20,000 - MUR 200,000+ (highly dependent on workload).
- Skilled Bioinformatician Salary (Annual): MUR 800,000 - MUR 2,500,000+ (depending on experience and seniority).
- Data Management and IT Support Personnel (Annual): MUR 600,000 - MUR 1,800,000+.
Key Considerations for Mauritius:
- Import Duties and Taxes: These can add a significant percentage to the cost of imported hardware and software.
- Local Vendor Support: Availability and cost of local technical support for hardware and software are crucial.
- Internet Bandwidth: Reliable and high-speed internet is vital for accessing cloud resources and transferring large datasets. The cost of such services can be a factor.
- Government and Institutional Funding: Research institutions and government bodies often play a key role in funding large-scale bioinformatics infrastructure, which influences the accessibility of these resources.
| Infrastructure Component | Estimated Range (MUR) | Notes |
|---|---|---|
| Entry-level Workstation/Server | 150,000 - 500,000 | For individual or small-scale local analysis. |
| Small to Medium HPC Cluster | 2,000,000 - 10,000,000+ | Scalable based on compute nodes, RAM, and storage. |
| High-Capacity Storage (e.g., 100 TB NAS) | 300,000 - 1,500,000+ | Cost increases with capacity and redundancy features. |
| Annual Commercial Software License (Basic Suite) | 50,000+ | Enterprise-level licenses can cost millions annually. |
| Cloud Computing (Monthly, Moderate Usage) | 20,000 - 200,000+ | Highly dependent on specific service usage and duration. |
| Annual Salary: Skilled Bioinformatician | 800,000 - 2,500,000+ | Varies significantly with experience and seniority. |
| Annual Salary: Data/IT Support Personnel | 600,000 - 1,800,000+ | Essential for infrastructure operation and maintenance. |
Key Factors Influencing Bioinformatics Infrastructure Costs in Mauritius
- Hardware Acquisition (Compute, Storage, Networking)
- Software Licensing (Commercial & Open-Source Support)
- Cloud Computing Services (Usage-Based)
- Data Management and Storage Volume
- Personnel and Skilled Expertise
- Maintenance, Updates, and Technical Support
- Import Duties, Taxes, and Local Markups
- Internet Connectivity and Bandwidth Costs
- Funding Availability (Government, Institutional, Grants)
Affordable Bioinformatics Infrastructure Options
Securing adequate bioinformatics infrastructure is crucial for research and development, yet often comes with significant costs. This document outlines affordable infrastructure options, emphasizing value bundles and cost-saving strategies to maximize research output while minimizing expenditure. We explore solutions ranging from cloud-based services to on-premises configurations, highlighting how strategic choices can lead to substantial financial benefits.
| Infrastructure Option | Value Proposition | Cost-Saving Strategy | Considerations |
|---|---|---|---|
| Cloud Computing (IaaS/PaaS) | Scalability, flexibility, reduced upfront hardware costs, access to specialized services (AI/ML, GPUs). | Utilize spot instances for non-critical, interruptible workloads. Leverage reserved instances or savings plans for predictable workloads. Optimize instance types and storage for specific tasks. Negotiate academic discounts. | Requires strong cloud management skills, potential for cost overruns if not monitored, data egress costs. |
| On-Premises HPC Clusters | Full control over hardware and data, no recurring cloud fees (after initial investment), potential for long-term cost efficiency for high, constant utilization. | Invest in energy-efficient hardware. Optimize cluster utilization to minimize idle time. Utilize open-source job schedulers and management tools. Consider refurbished hardware for non-critical components. | High upfront capital expenditure, requires dedicated IT expertise for maintenance and upgrades, slower to scale. |
| Hybrid Cloud Solutions | Combines the benefits of both cloud and on-premises, allowing for bursting to the cloud for peak loads while keeping sensitive data on-premises. | Use cloud for burst capacity, leverage on-premises for baseline workloads. Optimize data transfer between environments. Implement strong security policies for data in transit. | Increased complexity in management and integration, requires careful planning for data synchronization and security. |
| Containerization & Orchestration (Docker/Kubernetes) | Improves resource utilization, simplifies deployment and management, enables portability across different environments. | Reduces the need for dedicated virtual machines for each application, allowing for higher density and better hardware utilization. Automates scaling and resource allocation. | Requires learning new technologies, potential initial setup overhead. |
| Open-Source Software & Tools | Eliminates software licensing fees, vast community support and development. | Leverage powerful open-source alternatives for critical bioinformatics pipelines (e.g., Bioconductor, Galaxy, Snakemake). Utilize community support forums and documentation. | May require more technical expertise for installation and configuration, occasional support gaps compared to commercial software. |
| Managed Bioinformatics Services | Offloads infrastructure management and specialized tasks, allowing research teams to focus on scientific outcomes. | Pay only for the services used, reduces the need for in-house specialized IT staff. Can offer bundled pricing for common bioinformatics workflows. | Less control over underlying infrastructure, potential vendor lock-in, costs can accumulate for extensive usage. |
Key Value Bundles and Cost-Saving Strategies
- Cloud Computing Resource Bundles (e.g., AWS EC2 Spot Instances with reserved instances for stable workloads, Azure Hybrid Benefit)
- Open-Source Software Stack Optimization (leveraging free, community-supported tools)
- Shared Computing Resources (institutional HPC clusters, collaborative cloud projects)
- Containerization and Orchestration (Docker, Kubernetes for efficient resource utilization)
- Strategic Vendor Partnerships and Academic Discounts
- Data Storage Tiering and Archiving (moving less-accessed data to cheaper storage)
- Talent Development and Upskilling (training existing staff to manage and utilize infrastructure effectively)
- Scalable Pay-as-You-Go Models (avoiding large upfront investments for fluctuating needs)
- Leveraging Managed Services (outsourcing complex management tasks to cloud providers)
Verified Providers In Mauritius
Finding reliable healthcare providers is paramount for well-being. In Mauritius, Franance Health stands out as a premier network, distinguished by its rigorous credentialing process and commitment to quality care. This meticulous vetting ensures that every provider associated with Franance Health meets the highest standards of expertise, experience, and ethical practice. By choosing a Franance Health verified provider, you are opting for a healthcare professional who has undergone thorough background checks, license verification, and often peer reviews, guaranteeing a superior level of service and patient safety.
| Provider Category | Franance Health Verification Criteria | Benefits for Patients |
|---|---|---|
| General Practitioners | Valid medical license, proof of continuous professional development, malpractice insurance. | Access to trusted primary care physicians with up-to-date knowledge and ethical practice. |
| Specialists (e.g., Cardiologists, Dermatologists) | Board certification in specialty, extensive clinical experience, hospital affiliations, peer endorsements. | Consultation with highly experienced specialists offering advanced diagnostic and treatment options. |
| Hospitals and Clinics | Accreditation by recognized healthcare bodies, compliance with safety and quality standards, advanced medical equipment. | Receiving care in facilities that adhere to strict operational and patient care protocols, ensuring a safe and effective treatment environment. |
| Diagnostic Centers | Certified technicians and radiologists, calibration of equipment, adherence to quality control measures. | Reliable and accurate diagnostic results from well-equipped facilities with skilled professionals. |
Why Franance Health Credentials Matter:
- Rigorous Vetting Process: Franance Health implements a comprehensive credentialing system that goes beyond basic licensing, ensuring providers are highly qualified.
- Commitment to Quality: Their focus is on delivering exceptional healthcare standards, prioritizing patient outcomes and satisfaction.
- Enhanced Patient Safety: Verified providers have undergone thorough background checks and verification, reducing risks and ensuring trustworthy care.
- Access to Top-Tier Professionals: Franance Health connects you with leading medical practitioners across various specializations.
- Peace of Mind: Knowing your healthcare provider is accredited by a trusted entity like Franance Health offers significant reassurance.
Scope Of Work For Bioinformatics Infrastructure
This Scope of Work (SOW) outlines the requirements for the establishment and maintenance of a robust bioinformatics infrastructure. The objective is to provide a scalable, secure, and high-performance environment capable of supporting current and future genomic and proteomic data analysis needs. This includes hardware, software, networking, and storage solutions, along with associated maintenance and support services. The infrastructure will be designed to facilitate efficient data processing, storage, and collaboration among researchers. Key considerations include data security, regulatory compliance (e.g., HIPAA, GDPR if applicable), and ease of use for a diverse user base.
| Component | Specification | Quantity | Notes |
|---|---|---|---|
| HPC Compute Nodes | Minimum 16-core CPU per node, 64GB RAM per node, High-speed interconnect (e.g., InfiniBand) | 10 | Expandable as needed |
| HPC Head Node | Dual Xeon CPUs, 128GB RAM, SSD storage | 1 | Manages job scheduling and user access |
| Primary Data Storage | RAID 6 or equivalent, Minimum 500TB usable capacity, 10GbE or higher connectivity | 1 | Scalable to 1PB |
| Backup Storage | Deduplication enabled, Minimum 200TB usable capacity | 1 | Off-site replication is desirable |
| Bioinformatics Software Suite | GATK, BWA, Bowtie2, STAR, Salmon, FastQC, MultiQC, R/Bioconductor, Python (with relevant libraries like Biopython, Pandas, NumPy) | Licensed/Deployed | All versions to be compatible with the OS |
| Containerization Platform | Singularity or Docker Enterprise Edition | Deployed | Includes registry for image management |
| Network Switch | High-speed (40GbE/100GbE) non-blocking switch for cluster interconnect | 1 | With sufficient ports for compute nodes and storage |
| Firewall | Enterprise-grade Next-Generation Firewall (NGFW) | 1 | With VPN capabilities for remote access |
Technical Deliverables
- High-performance computing (HPC) cluster for sequence alignment, variant calling, and other computationally intensive analyses.
- Scalable and secure data storage solution (e.g., NAS, SAN, object storage) with appropriate backup and disaster recovery mechanisms.
- Dedicated bioinformatics software suite, including licensed and open-source tools for genomics, transcriptomics, proteomics, and epigenomics.
- Containerization platform (e.g., Docker, Singularity) for reproducible research and simplified software deployment.
- Data management and cataloging system for organizing, tracking, and accessing large genomic datasets.
- Secure remote access gateway for authorized users.
- Network infrastructure supporting high-bandwidth data transfer within the cluster and to external resources.
- Monitoring and logging system to track resource utilization, system health, and security events.
- User support and training materials for the bioinformatics infrastructure.
- Documentation for system architecture, configurations, and usage guidelines.
Service Level Agreement For Bioinformatics Infrastructure
This Service Level Agreement (SLA) outlines the expected response times and uptime guarantees for the Bioinformatics Infrastructure. This agreement is designed to ensure the reliable and efficient operation of the resources supporting bioinformatics research and development.
| Incident Severity | Uptime Guarantee | Response Time Target | Resolution Time Target (Best Effort) |
|---|---|---|---|
| Critical Incident | 99.9% Monthly Uptime | 1 Hour | 4 Hours |
| Major Incident | 99.9% Monthly Uptime | 2 Hours | 8 Hours |
| Minor Incident | 99.9% Monthly Uptime | 4 Business Hours | 2 Business Days |
Definitions
- Service Hours: The hours during which the Bioinformatics Infrastructure is expected to be fully operational and supported. This is defined as 24 hours a day, 7 days a week, 365 days a year.
- Downtime: Any period during Service Hours when the Bioinformatics Infrastructure is unavailable for use, excluding Scheduled Maintenance.
- Scheduled Maintenance: Pre-announced periods of planned downtime for system upgrades, patches, or essential maintenance. Notifications will be provided at least 48 hours in advance.
- Unscheduled Downtime: Any Downtime that is not Scheduled Maintenance.
- Response Time: The maximum time allowed for the support team to acknowledge and begin addressing a reported issue.
- Resolution Time: The maximum time allowed to fully resolve a reported issue. This may be an estimate and can be extended for complex issues with customer agreement.
- Critical Incident: An issue that renders a core service completely unusable, impacting a significant number of users or critical research activities.
- Major Incident: An issue that significantly degrades the performance or availability of a core service, impacting a subset of users or less critical research activities.
- Minor Incident: An issue that causes a minor inconvenience or impacts a single user or a small group of users without significantly affecting overall service availability.
Frequently Asked Questions
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