# ADR-0001 - Use Architectural Decision Records

## Date

2023-12-01

## Context

In a distributed team with many subteams, the best solution to communicate decisions is to use a format accessible by everyone in charge of development.

We use *Specification* and *Discovery* documents stored in Google Drive, but they present some downsides:

import static org.junit.jupiter.api.Assertions.assertEquals;

class CLIReportingUtilsTest {

    @Test
    void testFormatDuration() {
        assertEquals("0.001 s", CLIReportingUtils.formatDuration(1));
        assertEquals("0.999 s", CLIReportingUtils.formatDuration(1000 - 1));
        assertEquals("1.000 s", CLIReportingUtils.formatDuration(1000));
        assertEquals("59.999 s", CLIReportingUtils.formatDuration(60 * 1000 - 1));

          "datasource": {
            "type": "prometheus",
            "uid": "${datasource}"
          },
          "expr": "round(sum(irate(istio_requests_total{reporter=~\"$qrep\",destination_service=~\"$service\"}[5m])), 0.001)",
          "format": "time_series",
          "intervalFactor": 1,
          "refId": "A",
          "step": 4
        }
      ],
      "title": "Client Request Volume",
      "type": "stat"
    },

Our aim is to keep the process lightweight and approachable.

            "uid": "${datasource}"
          },
          "expr": "round(sum(irate(istio_requests_total{reporter=~\"$qrep\",destination_workload_namespace=~\"$namespace\",destination_workload=~\"$workload\"}[5m])), 0.001)",
          "format": "time_series",
          "intervalFactor": 1,
          "refId": "A",
          "step": 4
        }
      ],
      "title": "Incoming Request Volume",
      "type": "stat"
    },

        assertEquals(0, new BigDecimal("0.01").compareTo(BigDecimalConversionUtil.toBigDecimal(new Double(0.01D))));
        assertEquals(0, new BigDecimal("0.001").compareTo(BigDecimalConversionUtil.toBigDecimal(new Double(0.001D))));
        assertEquals(0, new BigDecimal("0.0001").compareTo(BigDecimalConversionUtil.toBigDecimal(new Double(0.0001D))));

// by dots suppressing leading zeros for IPv4 and the representation defined by RFC 5952 for IPv6.
// Valid: 192.168.1.5 or 2001:db8::1 or 2001:db8:aaaa:bbbb:cccc:dddd:eeee:1
// Invalid: 10.01.2.3 or 2001:db8:0:0:0::1
message IPAddress {
  // Standard object's metadata.
  // More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadata
  // +optional

        assertEquals("010203", StringUtil.toHex(new byte[] { 1, 2, 3 }));
    }

    /**
     * @throws Exception
     */
    @Test
    public void testToHex2() throws Exception {
        assertEquals("0001", StringUtil.toHex(1));
    }

    /**
     * @throws Exception
     */
    @Test
    public void testAppendHex() throws Exception {
        final StringBuilder buf = new StringBuilder();

    val a3 = "2001:db8::1:0:0:1"
    assertThat(parse("http://[2001:db8:0:0:1:0:0:1]").host).isEqualTo(a3)
    assertThat(parse("http://[2001:0db8:0:0:1:0:0:1]").host).isEqualTo(a3)
    assertThat(parse("http://[2001:db8::1:0:0:1]").host).isEqualTo(a3)
    assertThat(parse("http://[2001:db8::0:1:0:0:1]").host).isEqualTo(a3)
    assertThat(parse("http://[2001:0db8::1:0:0:1]").host).isEqualTo(a3)

  /**
   * Maximum allowed false positive probability of detecting a hash flooding attack given random
   * input.
   */
  @VisibleForTesting static final double HASH_FLOODING_FPP = 0.001;

  /**
   * Maximum allowed length of a hash table bucket before falling back to a j.u.HashMap based
   * implementation. Experimentally determined.
   */
  static final int MAX_HASH_BUCKET_LENGTH = 8;