tvvignesh

2020-01-30 15:44:10.211494 I | rookcmd: starting Rook v1.2.2 with arguments '/rook/rook ceph osd provision'
2020-01-30 15:44:10.211591 I | rookcmd: flag values: --cluster-id=86ba39f7-a91d-4e8a-ad05-7ec08d74c6f6, --data-device-filter=all, --data-device-path-filter=, --data-devices=, --data-directories=, --encrypted-device=false, --force-format=false, --help=false, --location=, --log-flush-frequency=5s, --log-level=INFO, --metadata-device=, --node-name=gke-tc-dev-1-tc-dev-big-2-74756ee2-34np, --operator-image=, --osd-database-size=0, --osd-journal-size=5120, --osd-store=, --osd-wal-size=576, --osds-per-device=1, --pvc-backed-osd=false, --service-account=
2020-01-30 15:44:10.211603 I | op-mon: parsing mon endpoints: c=10.104.0.218:6789,a=10.104.8.20:6789,b=10.104.12.173:6789
2020-01-30 15:44:10.224679 I | op-osd: CRUSH location=root=default host=gke-tc-dev-1-tc-dev-big-2-74756ee2-34np zone=asia-south1-a region=asia-south1
2020-01-30 15:44:10.224705 I | cephcmd: crush location of osd: root=default host=gke-tc-dev

tvvignesh

kind: Namespace
apiVersion: v1
metadata:
  name: dind
  labels:
    name: dind

---
apiVersion: v1
kind: PersistentVolumeClaim

tvvignesh

ff5c42c38ee7fdd410af696b7139c3a9e181fcf073c83c5f4268d5ccfab17b269b1d5377fc13a26e2d345f689f81bdb6dbcaeb465ed5c2a490049a0ce4f44626

tvvignesh

---
# Manually set metadata for the Release.
#
# Defaults to .Chart.Name
nameOverride: ""
# Defaults to .Release.Name-.Chart.Name unless .Release.Name contains "ambassador"
fullnameOverride: ""
# Defaults to .Release.Namespace
namespaceOverride: ""

tvvignesh

Time series data

1. https://www.analyticsvidhya.com/blog/2016/02/time-series-forecasting-codes-python/
2. http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html
3. https://machinelearningmastery.com/time-series-forecasting-methods-in-python-cheat-sheet/
4. https://www.analyticsvidhya.com/blog/2018/02/time-series-forecasting-methods/
5. https://www.youtube.com/watch?v=e8Yw4alG16Q
6. https://medium.com/@josemarcialportilla/using-python-and-auto-arima-to-forecast-seasonal-time-series-90877adff03c
7. https://www.digitalocean.com/community/tutorials/a-guide-to-time-series-forecasting-with-arima-in-python-3
8. https://www.sciencedirect.com/science/article/pii/S0925231217309864
9. http://publications.lib.chalmers.se/records/fulltext/242944/242944.pdf

tvvignesh

---
# Source: dgraph/templates/alpha/configs.yaml
apiVersion: v1
kind: ConfigMap
metadata:
  name: dgraph-dgraph-alpha-config
  labels:
    app: dgraph
    chart: dgraph-0.0.11
    component: alpha

tvvignesh

/**
 * Grant options
 */
export interface GrantOptions {
  /**
   * Handler name
   */
  handler?: 'express' | 'koa' | 'hapi' | 'fastify' | 'curveball' |
            'node' | 'aws' | 'azure' | 'gcloud' | 'vercel'

tvvignesh

importers:
  .:
    dependencies:
      '@graphql-mesh/cache-file': 0.4.21_graphql@15.4.0
      '@graphql-mesh/cli': 0.11.11_graphql@15.4.0
      '@graphql-mesh/config': 0.10.16_graphql@15.4.0
      '@graphql-mesh/graphql': 0.7.9_graphql@15.4.0
      '@graphql-mesh/runtime': 0.7.15_graphql@15.4.0
      '@graphql-mesh/transform-prefix': 0.5.19_graphql@15.4.0
      '@graphql-tools/utils': 7.0.2_graphql@15.4.0

tvvignesh

importers:
  .:
    dependencies:
      '@graphql-mesh/cache-file': 0.4.30_graphql@15.4.0
      '@graphql-mesh/cli': 0.15.0_graphql@15.4.0
      '@graphql-mesh/config': 0.11.8_graphql@15.4.0
      '@graphql-mesh/graphql': 0.10.5_graphql@15.4.0
      '@graphql-mesh/runtime': 0.10.8_graphql@15.4.0
      '@graphql-tools/utils': 7.2.0_graphql@15.4.0
      fetchache: 0.0.4

tvvignesh

importers:
  .:
    dependencies:
      '@graphql-mesh/cache-file': 0.4.48_graphql@15.5.0
      '@graphql-mesh/cli': 0.15.7_graphql@15.5.0
      '@graphql-mesh/config': 0.11.20_graphql@15.5.0
      '@graphql-mesh/graphql': 0.12.1_graphql@15.5.0
      '@graphql-mesh/runtime': 0.10.26_graphql@15.5.0
      '@graphql-tools/utils': 7.2.5_graphql@15.5.0
      fetchache: 0.0.4